CN107908109A - A kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration optimization - Google Patents

A kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration optimization Download PDF

Info

Publication number
CN107908109A
CN107908109A CN201711116197.5A CN201711116197A CN107908109A CN 107908109 A CN107908109 A CN 107908109A CN 201711116197 A CN201711116197 A CN 201711116197A CN 107908109 A CN107908109 A CN 107908109A
Authority
CN
China
Prior art keywords
aircraft
mrow
angle
flight
hypersonic
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201711116197.5A
Other languages
Chinese (zh)
Other versions
CN107908109B (en
Inventor
刘兴高
刘平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN201711116197.5A priority Critical patent/CN107908109B/en
Publication of CN107908109A publication Critical patent/CN107908109A/en
Application granted granted Critical
Publication of CN107908109B publication Critical patent/CN107908109B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)

Abstract

The invention discloses a kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration, which is made of aircraft altitude height sensor, aircraft speed sensor, aircraft flight navigation channel obliquity sensor, the horizontal flying distance sensor of aircraft, aircraft micro-control unit (MCU), Aircraft Angle of Attack controller.Aircraft MCU requires automated execution inner orthogonal configuration optimization algorithm according to the height above sea level, speed, flight path angle of setting, obtain making hypersonic aircraft horizontal flight that the control strategy of acquisition are converted to control instruction and be sent to the execution of Aircraft Angle of Attack controller apart from longest track optimizing control strategy, aircraft MCU.The present invention can be quickly obtained track optimizing control strategy according to the different height above sea level of hypersonic aircraft, speed, flight path angle and flight horizontal distance state, hypersonic aircraft is obtained longer horizontal flight distance.

Description

A kind of hypersonic aircraft reentry stage track optimizing control based on orthogonal configuration optimization Device processed
Technical field
It is mainly a kind of to be optimized based on orthogonal configuration the present invention relates to hypersonic aircraft reentry stage track optimizing field Hypersonic aircraft reentry stage track optimizing controller.Fast height can be provided after hypersonic aircraft reaches reentry stage Supersonic aircraft track optimizing control strategy is simultaneously converted to Aircraft Angle of Attack control instruction, hypersonic aircraft is obtained more Long horizontal flight distance.
Background technology
Hypersonic aircraft is to realize long-range quick precision strike and the course of new aircraft that the whole world quickly reaches, in future Military affairs, there is highly important strategic position in politics and economy, it is extremely heavy to have become one, Global Aerospace field The developing direction wanted, research and development hypersonic aircraft have very important meaning in terms of exploiting outer space and national security Justice.
In the research of hypersonic aircraft, track optimizing is that contemporary aircraft design and the important appearance controlled not only have Beneficial to raising aircraft flight quality to meet assigned tasks requirement, while it is also important guarantee and the realization for completing aerial mission The necessary condition of maneuvering flight, was constantly subjected to the attention of domestic and international each military power, currently studied both at home and abroad in recent years Hot and difficult issue.
Due to entering atmosphere from air from outer rim, highly very big with the excursion of speed, hypersonic aircraft face Face various severe reentry environments, reentry stage track optimizing technology is then to ensure that hypersonic aircraft completes the pass of aerial mission Key, has prior practical value to improving its strike scope and impact accuracy.Therefore, efficient hypersonic flight is studied Device reentry stage track optimizing method is particularly important.
The content of the invention
In order to make hypersonic aircraft obtain longer horizontal flight distance, the strike model of hypersonic aircraft is improved Enclose, the present invention provides a kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration optimization.
The purpose of the present invention is what is be achieved through the following technical solutions:It is a kind of based on orthogonal configuration optimization it is hypersonic Aircraft reentry stage track optimizing controller, according to the initial height above sea level of hypersonic aircraft reentry stage, speed, Flight Path Inclination angle and flight horizontal distance state rapidly obtain track optimizing control strategy, hypersonic by controlling Aircraft Angle of Attack to make Aircraft obtains longer horizontal flight distance.Flown by aircraft altitude height sensor, aircraft speed sensor, aircraft The horizontal flying distance sensor of row navigation channel obliquity sensor, aircraft, aircraft micro-control unit (MCU), Aircraft Angle of Attack control Device processed is formed.Each part is connected by data/address bus in hypersonic aircraft, and the operational process of described device includes:
Step 1):Aerodynamic Parameter Model, aircraft of the input corresponding to the aircraft in hypersonic aircraft MCU Can constraints, specified optimization aim;
Step 2):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor, aircraft speed are opened Sensor, aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft, obtain hypersonic aircraft Current height above sea level, speed, flight path angle and flight horizontal distance status information;
Step 3):Aircraft MCU is required inside automated execution according to the height above sea level, speed, flight path angle of setting Orthogonal configuration optimizes algorithm, obtains making hypersonic aircraft horizontal flight apart from longest track optimizing control strategy;
Step 4):The track optimizing control strategy of acquisition is sent to control strategy output mould by hypersonic aircraft MCU Block, and be converted to control instruction and be sent to the execution of Aircraft Angle of Attack controller.
The hypersonic aircraft MCU parts include information acquisition module 21, initialization module 22, ODE Group (Ordinary Differential Equations, abbreviation ODE) orthogonal configuration module 23, Non-Linear Programming (Non- Linear Programming, abbreviation NLP) problem solver module 24, control instruction output module 25.Wherein, information gathering mould Block includes aircraft altitude height and speed acquisition, aircraft flight navigation channel inclination angle and flight horizontal distance collection, aircraft sea Degree of lifting and speed setting collection, the collection of aircraft flight navigation channel angle set, the Aerodynamic Parameter Model of aircraft and performance are about Beam condition and specified predetermined optimizing target parameter gather five submodules;NLP, which solves module, includes search direction solution, optimizing step-length Solution, optimizing amendment, NLP convergences judge four submodules.
Hypersonic aircraft reentry stage track optimizing problem can be described as
Max J [u (t)]=x4(tf)
x1(t0)=h0,x2(t0)=v0,x3(t0)=γ0,x4(t0)=r0
x1(tf)=hf,x2(tf)=vf,x3(tf)=γf
G[u(t),x(t),t]≥0
umin≤u(t)≤umax
Wherein t represents the time, and x (t) represents the state variable of hypersonic aircraft, x1(t) represent that aircraft altitude is high Degree, x2(t) aircraft speed, x are represented3(t) aircraft flight navigation channel inclination angle, x are represented4(t) represent aircraft horizontal flight away from From u (t) represents the angle of attack controlled quentity controlled variable of hypersonic aircraft, is the control variable of this problem;Represent state variable x (t) First derivative, F (x (t), u (t), t) is the differential according to hypersonic aircraft reentry stage three-dimensional space motion establishing equation Equation group mathematical model;t0Represent the time point that reentry stage track optimizing starts, h0Represent the initial of optimization start time aircraft Height above sea level, v0Represent the initial velocity of optimization start time aircraft, γ0Represent that the initial of optimization start time aircraft flies Row navigation channel angle, r0Represent the initial level flying distance of optimization start time aircraft, tfAt the end of representing reentry stage track optimizing Between point, hfRepresent the height above sea level of optimization finish time aircraft, vfRepresent the speed of optimization finish time aircraft, γfRepresent Optimize the Flight Path angle of finish time aircraft;J [u (t)] represents that the object function of hypersonic aircraft track optimizing is Optimize the horizontal flight distance of finish time aircraft, G [u (t), x (t), t] is the pact of hypersonic aircraft reentry stage process Beam condition, uminAnd umaxRepresent the lower limit and upper limit value of angle of attack control range.
The technical solution adopted by the present invention to solve the technical problems is:In hypersonic aircraft micro-control unit (MCU) orthogonal configuration optimization algorithm (Orthogonal collocation, abbreviation OC) is integrated with, in hypersonic aircraft The control instruction of fast Aircraft Angle of Attack can be provided after arrival reentry stage, hypersonic aircraft is obtained longer horizontal flight Distance.
The MCU can be considered as automatic control signal generator, which includes Aerodynamic Parameter Model, aircraft performance Constraints, specify optimization aim setting module 11, hypersonic aircraft MCU module 12, aircraft altitude height sensor 13, aircraft speed sensor 14, aircraft flight navigation channel obliquity sensor 15, the horizontal flying distance sensor 16 of aircraft, Aircraft altitude height, speed, flight path angle setting module 17, Aircraft Angle of Attack control 18, each group in the system Connected into part by data/address bus in controller.
The operational process of the controller is as follows:
Step 1):The controller is installed on certain type hypersonic aircraft, and is inputted in aircraft MCU 12 Aerodynamic Parameter Model, aircraft performance constraints, specified predetermined optimizing target parameter information 11 corresponding to aircraft;
Step 2):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor 13, aircraft speed pass Sensor 14, aircraft flight navigation channel obliquity sensor 15 and the horizontal flying distance sensor 16 of aircraft, obtain hypersonic fly The current height above sea level of row device, speed, flight path angle and flight horizontal distance status information;
Step 3):Aircraft MCU12 is obtained according to aircraft altitude height, speed, flight path angle setting module 17 Control targe information, MCU module 12 perform the orthogonal configuration optimization algorithm of inside, obtain making the horizontal flying distance of aircraft farthest TRAJECTORY CONTROL strategy;
Step 4):The control strategy of acquisition is converted to angle of attack control instruction and exported to Aircraft Angle of Attack control by aircraft MCU Device module 18 processed;
The hypersonic aircraft MCU for being integrated with orthogonal configuration optimization algorithm is the core of the present invention, it is internal including letter Cease acquisition module 21, initialization module 22, ODE orthogonal configurations module 23, NLP problem solver modules 24, control instruction output mould Block 25.Wherein, information acquisition module includes current flight device height above sea level and speed acquisition, current flight device flight path angle Gather, fly with the collection of flight horizontal distance, aircraft altitude height and speed setting collection, aircraft flight navigation channel angle set The Aerodynamic Parameter Model and performance constraints of row device and specified predetermined optimizing target parameter gather five submodules;NLP solves mould Block judges four submodules including search direction solution, the solution of optimizing step-length, optimizing amendment, NLP convergences.
The hypersonic aircraft MCU automatically generates the orthogonal configuration optimization algorithm operating procedure of angle of attack control instruction It is as follows:
Step 1):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor, aircraft speed sensing Device, aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft are opened, and information acquisition module 21 obtains The current height above sea level of hypersonic aircraft, speed, flight path angle and flight horizontal distance status information;
Step 2):Initialization module 22 brings into operation, and sets discrete hop count, the angle of attack controlled quentity controlled variable of track optimizing process time Initial guess u(0)(t), the initial value x of state trajectory(0)(t), setting optimization required precision tol, iterations k is put Zero;
Step 3):By ODE orthogonal configurations module 23 by ordinary differential system in time shaft [t0,tf] on all it is discrete;
Step 4):Required angle of attack control strategy and corresponding states track are obtained by NLP problem solver modules 24, this Process includes multiple inner iterative, and each iteration will solve search direction and optimizing step-length, and carry out optimizing amendment.To Mr. Yu The angle of attack controlled quentity controlled variable u that an iteration obtains(k)(t), if it corresponds to target function value J [u(k)(t)] with the mesh of preceding an iteration Offer of tender numerical value J [u(k-1)(t)] difference is less than required precision tol, then judges convergence sexual satisfaction, and by angle of attack controlled quentity controlled variable u(k)(t) make Control strategy output module 25 is output to for instruction.
The ODE orthogonal configuration modules, are realized using following steps:
Step 1):Angle of attack controlled quentity controlled variable u (t), state trajectory x (t) are represented with the linear combination of M rank basic functions, i.e.,:
Wherein N is time shaft [t0,tf] discrete hop count, φ (t) is Lagrange's interpolation basic function, linear combination coefficient ui,jAnd si,jIt is u (t) and x (t) respectively in collocation point ti,jOn value.
Step 2):Due to all basic functions derived function expression formula it is known that then the differential equation group of state trajectory by from Dispersion quantic:
Step 3):Original differential equation group is replaced with the differential equation group after discretization, NLP problems to be asked will be obtained.
The NLP solves module, is realized using following steps:
Step 1):By angle of attack controlled quentity controlled variable u(k-1)(t) as some point in vector space, it is denoted as P1, P1Corresponding target Functional value is exactly J [u(k-1)(t)];
Step 2):From point P1Set out, according to the NLP algorithms of selection, construct a search direction in vector space to d(k -1)With step-length α(k-1)
Step 3):Pass through formula u(k)(t)=u(k-1)(t)+α(k-1)d(k-1)U is corresponded in construction vector space(k)Another Point P2So that P2Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent.
Step 4):U is corrected using optimizing(k)(t), the point after being correctedIt is denoted as point P3, with seasonSo that P3Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent;
Step 5):If the target function value J [u of current iteration(k)(t)] with the target function value J [u of last iteration(k -1)(t)] difference of absolute value is less than precision tol, then judges convergence sexual satisfaction, the control strategy u that current iteration is obtained(k)(t) Export to control strategy output module 25;If convergence is unsatisfactory for, iterations k increases by 1, by u(k)(t) it is arranged to initial Value, continues to execute step 2).
Beneficial effects of the present invention are mainly manifested in:Since orthogonal collocation method possesses more accurate capability of fitting, can obtain Obtain the accurate solution of hypersonic aircraft reentry trajectory optimization;Employ search direction solution, optimizing step-length solves, optimizing is repaiied Just, NLP convergences determination strategy, the solution of approximate NLP problems will gradually approach the optimal solution of former problem;Since this method is not required to Dynamical equation is solved repeatedly, can obtain faster convergence rate, reduced and obtained the optimization of hypersonic aircraft reentry trajectory The calculating time of optimal control policy.The present invention can be such that hypersonic aircraft horizontal flight is attacked apart from longer track optimizing Angle control instruction, improves hypersonic aircraft strike scope.
Brief description of the drawings
Fig. 1 is the structure diagram of the present invention;
Fig. 2 is hypersonic aircraft MCU internal module structure charts of the present invention;
Fig. 3 is the angle of attack control strategy curve map of embodiment 1;
Fig. 4 is the corresponding horizontal flight distance map of angle of attack control strategy of embodiment 1.
Embodiment
Hypersonic aircraft reentry stage track optimizing problem can be described as
Max J [u (t)]=x4(tf)
x1(t0)=h0,x2(t0)=v0,x3(t0)=γ0,x4(t0)=r0
x1(tf)=hf,x2(tf)=vf,x3(tf)=γf
G[u(t),x(t),t]≥0
umin≤u(t)≤umax
Wherein t represents the time, and x (t) represents the state variable of hypersonic aircraft, x1(t) represent that aircraft altitude is high Degree, x2(t) aircraft speed, x are represented3(t) aircraft flight navigation channel inclination angle, x are represented4(t) represent aircraft horizontal flight away from From u (t) represents the angle of attack controlled quentity controlled variable of hypersonic aircraft, is the control variable of this problem;Represent state variable x (t) First derivative, F (x (t), u (t), t) is the differential according to hypersonic aircraft reentry stage three-dimensional space motion establishing equation Equation group mathematical model;t0Represent the time point that reentry stage track optimizing starts, h0Represent the initial of optimization start time aircraft Height above sea level, v0Represent the initial velocity of optimization start time aircraft, γ0Represent that the initial of optimization start time aircraft flies Row navigation channel angle, r0Represent the initial level flying distance of optimization start time aircraft, tfAt the end of representing reentry stage track optimizing Between point, hfRepresent the height above sea level of optimization finish time aircraft, vfRepresent the speed of optimization finish time aircraft, γfRepresent Optimize the Flight Path angle of finish time aircraft;J [u (t)] represents that the object function of hypersonic aircraft track optimizing is Optimize the horizontal flight distance of finish time aircraft, G [u (t), x (t), t] is the pact of hypersonic aircraft reentry stage process Beam condition, uminAnd umaxRepresent the lower limit and upper limit value of angle of attack control range.
The technical solution adopted by the present invention to solve the technical problems is:In hypersonic aircraft micro-control unit (MCU) orthogonal configuration optimization algorithm (Orthogonal collocation, abbreviation OC) is integrated with, in hypersonic aircraft The control instruction of fast Aircraft Angle of Attack can be provided after arrival reentry stage, hypersonic aircraft is obtained longer horizontal flight Distance.
The MCU can be considered as automatic control signal generator, the controller as shown in Figure 1, including Aerodynamic Parameter Model, Aircraft performance constraints, specify optimization aim setting module 11, hypersonic aircraft MCU module 12, aircraft altitude Height sensor 13, aircraft speed sensor 14, aircraft flight navigation channel obliquity sensor 15, the horizontal flying distance of aircraft Sensor 16, aircraft altitude height, speed, flight path angle setting module 17, Aircraft Angle of Attack control 18, the system Interior each part is connected by data/address bus in controller.
The operational process of the controller is as follows:
Step 1):The controller is installed on certain type hypersonic aircraft, and is inputted in aircraft MCU 12 Aerodynamic Parameter Model, aircraft performance constraints, specified predetermined optimizing target parameter information 11 corresponding to aircraft;
Step 2):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor 13, aircraft speed pass Sensor 14, aircraft flight navigation channel obliquity sensor 15 and the horizontal flying distance sensor 16 of aircraft, obtain hypersonic fly The current height above sea level of row device, speed, flight path angle and flight horizontal distance status information;
Step 3):Aircraft MCU12 is obtained according to aircraft altitude height, speed, flight path angle setting module 17 Control targe information, MCU module 12 perform the orthogonal configuration optimization algorithm of inside, obtain making the horizontal flying distance of aircraft farthest TRAJECTORY CONTROL strategy;
Step 4):The control strategy of acquisition is converted to angle of attack control instruction and exported to Aircraft Angle of Attack control by aircraft MCU Device module 18 processed;
The hypersonic aircraft MCU for being integrated with orthogonal configuration optimization algorithm is the core of the present invention, as shown in Fig. 2, its Inside includes information acquisition module 21, initialization module 22, ODE orthogonal configurations module 23, NLP problem solver modules 24, control Command output module 25.Wherein, information acquisition module includes current flight device height above sea level and speed acquisition, current flight device fly Row navigation channel inclination angle and flight horizontal distance collection, aircraft altitude height and speed setting collection, aircraft flight navigation channel inclination angle Setting collection, the Aerodynamic Parameter Model of aircraft and performance constraints and specified predetermined optimizing target parameter gather five submodules Block;NLP solves module and judges four submodules including search direction solution, the solution of optimizing step-length, optimizing amendment, NLP convergences.
The hypersonic aircraft MCU automatically generates the orthogonal configuration optimization algorithm operating procedure of angle of attack control instruction It is as follows:
Step 1):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor, aircraft speed sensing Device, aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft are opened, and information acquisition module 21 obtains The current height above sea level of hypersonic aircraft, speed, flight path angle and flight horizontal distance status information;
Step 2):Initialization module 22 brings into operation, and sets discrete hop count, the angle of attack controlled quentity controlled variable of track optimizing process time Initial guess u(0)(t), the initial value x of state trajectory(0)(t), setting optimization required precision tol, iterations k is put Zero;
Step 3):By ODE orthogonal configurations module 23 by ordinary differential system in time shaft [t0,tf] on all it is discrete;
Step 4):Required angle of attack control strategy and corresponding states track are obtained by NLP problem solver modules 24, this Process includes multiple inner iterative, and each iteration will solve search direction and optimizing step-length, and carry out optimizing amendment.To Mr. Yu The angle of attack controlled quentity controlled variable u that an iteration obtains(k)(t), if it corresponds to target function value J [u(k)(t)] with the mesh of preceding an iteration Offer of tender numerical value J [u(k-1)(t)] difference is less than required precision tol, then judges convergence sexual satisfaction, and by angle of attack controlled quentity controlled variable u(k)(t) make Control strategy output module 25 is output to for instruction.
The ODE orthogonal configuration modules, are realized using following steps:
Step 1):Angle of attack controlled quentity controlled variable u (t), state trajectory x (t) are represented with the linear combination of M rank basic functions, i.e.,:
Wherein N is time shaft [t0,tf] discrete hop count, φ (t) is Lagrange's interpolation basic function, linear combination coefficient ui,jAnd si,jIt is u (t) and x (t) respectively in collocation point ti,jOn value.
Step 2):Due to all basic functions derived function expression formula it is known that then the differential equation group of state trajectory by from Dispersion quantic:
Step 3):Original differential equation group is replaced with the differential equation group after discretization, NLP problems to be asked will be obtained.
The NLP solves module, is realized using following steps:
Step 1):By angle of attack controlled quentity controlled variable u(k-1)(t) as some point in vector space, it is denoted as P1, P1Corresponding target Functional value is exactly J [u(k-1)(t)];
Step 2):From point P1Set out, according to the NLP algorithms of selection, construct a search direction in vector space to d(k -1)With step-length α(k-1)
Step 3):Pass through formula u(k)(t)=u(k-1)(t)+α(k-1)d(k-1)U is corresponded in construction vector space(k)Another Point P2So that P2Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent.
Step 4):U is corrected using optimizing(k)(t), the point after being correctedIt is denoted as point P3, with seasonSo that P3Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent;
Step 5):If the target function value J [u of current iteration(k)(t)] with the target function value J [u of last iteration(k -1)(t)] difference of absolute value is less than precision tol, then judges convergence sexual satisfaction, the control strategy u that current iteration is obtained(k)(t) Export to control strategy output module 25;If convergence is unsatisfactory for, iterations k increases by 1, by u(k)(t) it is arranged to initial Value, continues to execute step 2).
Embodiment 1
Hypersonic aircraft reaches reentry stage spatial domain, hypersonic aircraft altitude sensor, velocity sensor, Flight path angle sensor, horizontal flight range sensor and MCU have turned on.Information acquisition module gathers aircraft immediately Initial height above sea level, speed, flight path angle and horizontal flight distance during into reentry stage, if current initial time t0= 0s, the height above sea level that altitude sensor is passed to MCU are h0=80 000m, the speed that velocity sensor is passed to MCU are v0= 6400m/s, the flight path angle that flight path angle sensor is passed to MCU are γ0=-0.052rad, horizontal flight distance The horizontal flight distance that sensor sensor is passed to MCU is r0=0m;Final value moment tfHypersonic aircraft needs the condition met It is set as h for height above sea levelf=24000m, speed are set as vf=760m/s, flight path angle are set as γf=- 0.08rad;With reference to the three-dimensional space motion equation of aircraft, Aerodynamic Parameter Model, aircraft performance constraints and specify excellent Change target, the mathematical model for obtaining the problem is as follows:
Max J [u (t)]=x4(tf)
CL=-0.15+3.44u (t)
CD=0.29-1.51u (t)+5.87u (t)2
x1(0)=80 × 103,x1(tf)=24 × 103
x2(0)=6.4 × 103,x2(tf)=760
x3(0)=- 0.052, x3(tf)=- 0.08
x4(0)=0
-15≤u(t)≤30
Wherein L represents lift, and D represents resistance, CLRepresent lift coefficient, CDRepresent resistance coefficient.For the ease of statement, adopt The differential equation group mathematics of hypersonic aircraft reentry stage three-dimensional space motion establishing equation is represented with F (x (t), u (t), t) Model, i.e.,:
The constraints of hypersonic aircraft reentry stage process is represented using G [u (t), x (t), t], is:
In addition, J [u (t)] represents that the object function of hypersonic aircraft track optimizing optimizes finish time aircraft Horizontal flight distance.
Hypersonic aircraft MCU automatically generates the orthogonal configuration optimization algorithm of angle of attack control instruction as shown in Fig. 2, it is transported Row step is as follows:
Step 1):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor, aircraft speed sensing Device, aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft are opened, and information acquisition module 21 obtains Initial time t0Hypersonic aircraft height above sea level h during=0s0=80 000m, speed v0=6400m/s, Flight Path incline Angle is γ0=-0.052rad, horizontal flight range sensor sensor horizontal flight distance are arranged to r0=0m;Final value moment tfIt is high The requirement of supersonic aircraft height above sea level is set as hf=24000m, rate request are set as vf=760m/s, flight path angle It is required that it is set as γf=-0.08rad;;
Step 2):Initialization module 22 brings into operation, and the discrete hop count for setting track optimizing process time is 10, angle of attack control The initial guess u of amount processed(0)(t)=0.5, setting optimization required precision tol=10-8, by iterations k zero setting;
Step 3):By ODE orthogonal configurations module 23 by ordinary differential system in time shaft [t0,tf] on all it is discrete;
Step 4):Required angle of attack control strategy and corresponding states track are obtained by NLP problem solver modules 24, this Process includes multiple inner iterative, and each iteration will solve search direction and optimizing step-length, and carry out optimizing amendment.To Mr. Yu The angle of attack controlled quentity controlled variable u that an iteration obtains(k)(t), if it corresponds to target function value J [u(k)(t)] with the mesh of preceding an iteration Offer of tender numerical value J [u(k-1)(t)] difference is less than required precision 10-8, then judge convergence sexual satisfaction, and by angle of attack controlled quentity controlled variable u(k)(t) Control strategy output module 25 is output to as instruction.
The ODE orthogonal configuration modules, are realized using following steps:
Step 1):Angle of attack controlled quentity controlled variable u (t), state trajectory x (t) are represented with the linear combination of 3 rank basic functions, i.e.,:
Wherein N is time shaft [t0,tf] discrete hop count, φ (t) is Lagrange's interpolation basic function, linear combination coefficient ui,jAnd si,jIt is u (t) and x (t) respectively in collocation point ti,jOn value.
Step 2):Due to all basic functions derived function expression formula it is known that then the differential equation group of state trajectory by from Dispersion quantic:
Step 3):Original differential equation group is replaced with the differential equation group after discretization, NLP problems to be asked will be obtained.
The NLP solves module, is realized using following steps:
Step 1):By angle of attack controlled quentity controlled variable u(k-1)(t) as some point in vector space, it is denoted as P1, P1Corresponding target Functional value is exactly J [u(k-1)(t)];
Step 2):From point P1Set out, according to the NLP algorithms of selection, construct a search direction in vector space to d(k -1)With step-length α(k-1)
Step 3):Pass through formula u(k)(t)=u(k-1)(t)+α(k-1)d(k-1)U is corresponded in construction vector space(k)Another Point P2So that P2Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent.
Step 4):U is corrected using optimizing(k)(t), the point after being correctedIt is denoted as point P3, with seasonSo that P3Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent;
Step 5):If the target function value J [u of current iteration(k)(t)] with the target function value J [u of last iteration(k -1)(t)] difference of absolute value is less than precision 10-8, then convergence sexual satisfaction, the control strategy u that current iteration is obtained are judged(k)(t) Export to control strategy output module 25;If convergence is unsatisfactory for, iterations k increases by 1, by u(k)(t) it is arranged to initial Value, continues to execute step 2).
Finally, the optimization track of acquisition is output to control strategy output module by aircraft MCU as instruction, is converted to control Instruction processed is sent to angle of attack controller, completes the execution of track optimizing.Fig. 3 is the angle of attack control strategy curve map of embodiment 1;Figure 4 be the corresponding horizontal flight distance map of angle of attack control strategy of embodiment 1.
Above content is that a further detailed description of the present invention in conjunction with specific preferred embodiments, it is impossible to is assert The specific implementation of the present invention is only limited to these explanations.For general technical staff of the technical field of the invention, not On the premise of departing from inventive concept, some simple deduction or replace can also be made, should all be considered as belonging to the protection of the present invention Scope.

Claims (1)

1. a kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration optimization, flies according to hypersonic The initial height above sea level of row device reentry stage, speed, flight path angle and flight horizontal distance state rapidly obtain track optimizing Control strategy, by controlling Aircraft Angle of Attack to make hypersonic aircraft obtain longer horizontal flight distance.It is characterized in that: It is horizontal winged by aircraft altitude height sensor, aircraft speed sensor, aircraft flight navigation channel obliquity sensor, aircraft Row distance sensor, aircraft micro-control unit (MCU), Aircraft Angle of Attack controller are formed.Each part is by high ultrasound Data/address bus connects in fast aircraft, and the operational process of described device includes:
Step 1):Input corresponds to the Aerodynamic Parameter Model of the aircraft, aircraft performance about in hypersonic aircraft MCU Beam condition, specify optimization aim;
Step 2):After hypersonic aircraft reaches reentry stage, aircraft altitude height sensor, aircraft speed sensing are opened Device, aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft, it is current to obtain hypersonic aircraft Height above sea level, speed, flight path angle and flight horizontal distance status information;
Step 3):Aircraft MCU requires automated execution inner orthogonal according to the height above sea level, speed, flight path angle of setting Configuration optimization algorithm, obtains making hypersonic aircraft horizontal flight apart from longest track optimizing control strategy;
Step 4):The track optimizing control strategy of acquisition is sent to control strategy output module by hypersonic aircraft MCU, and Be converted to control instruction and be sent to the execution of Aircraft Angle of Attack controller.
The hypersonic aircraft MCU parts include information acquisition module 21, initialization module 22, ordinary differential system (Ordinary Differential Equations, abbreviation ODE) orthogonal configuration module 23, Non-Linear Programming (Non-linear Programming, abbreviation NLP) problem solver module 24, control instruction output module 25.Wherein, information acquisition module includes flying Row device height above sea level and speed acquisition, aircraft flight navigation channel inclination angle and the collection of flight horizontal distance, aircraft altitude height and Speed setting collection, the collection of aircraft flight navigation channel angle set, the Aerodynamic Parameter Model of aircraft and performance constraints with And specified predetermined optimizing target parameter gathers five submodules;NLP, which solves module, to be included search direction solution, the solution of optimizing step-length, seeks Excellent amendment, NLP convergences judge four submodules.
The hypersonic aircraft MCU automatically generates the orthogonal configuration optimization algorithm operating procedure of angle of attack control instruction such as Under:
Step 1):Hypersonic aircraft reach reentry stage after, aircraft altitude height sensor, aircraft speed sensor, Aircraft flight navigation channel obliquity sensor and the horizontal flying distance sensor of aircraft are opened, and information acquisition module 21 obtains superb The current height above sea level of velocity of sound aircraft, speed, flight path angle and flight horizontal distance status information;
Step 2):Initialization module 22 brings into operation, set the discrete hop count of track optimizing process time, angle of attack controlled quentity controlled variable just Beginning conjecture value u(0)(t), setting optimization required precision tol, by iterations k zero setting;
Step 3):By ODE orthogonal configurations module 23 by ordinary differential system in time shaft [t0,tf] on all it is discrete;
Step 4):Required angle of attack control strategy and corresponding states track, this process are obtained by NLP problem solver modules 24 Including multiple inner iterative, each iteration will solve search direction and optimizing step-length, and carry out optimizing amendment.For certain once The angle of attack controlled quentity controlled variable u that iteration obtains(k)(t), if it corresponds to target function value J [u(k)(t)] with the target letter of preceding an iteration Numerical value J [u(k-1)(t)] difference is less than required precision tol, then judges convergence sexual satisfaction, and by angle of attack controlled quentity controlled variable u(k)(t) it is used as and refers to Order is output to control strategy output module 25.
The ODE orthogonal configuration modules, are realized using following steps:
Step 1):Angle of attack controlled quentity controlled variable u (t), state trajectory x (t) are represented with the linear combination of M rank basic functions, i.e.,:
<mrow> <mi>u</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;ap;</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <msubsup> <mi>&amp;phi;</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mrow> <mo>(</mo> <mi>M</mi> <mo>)</mo> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>N</mi> </mrow>
<mrow> <mi>x</mi> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;ap;</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <msubsup> <mi>&amp;phi;</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mrow> <mo>(</mo> <mi>M</mi> <mo>)</mo> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>N</mi> </mrow>
Wherein N is time shaft [t0,tf] discrete hop count, φ (t) is Lagrange's interpolation basic function, linear combination coefficient ui,jWith si,jIt is u (t) and x (t) respectively in collocation point ti,jOn value.
Step 2):Since the derived function expression formula of all basic functions is it is known that then the differential equation group of state trajectory is discretized Quantic:
<mrow> <mover> <mi>x</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;ap;</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <msubsup> <mover> <mi>&amp;phi;</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mrow> <mo>(</mo> <mi>M</mi> <mo>)</mo> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>N</mi> </mrow>
Step 3):Original differential equation group is replaced with the differential equation group after discretization, NLP problems to be asked will be obtained.
The NLP solves module, is realized using following steps:
Step 1):By angle of attack controlled quentity controlled variable u(k-1)(t) as some point in vector space, it is denoted as P1, P1Corresponding target function value It is exactly J [u(k-1)(t)];
Step 2):From point P1Set out, according to the NLP algorithms of selection, construct a search direction in vector space to d(k-1)With Step-length α(k-1)
Step 3):Pass through formula u(k)(t)=u(k-1)(t)+α(k-1)d(k-1)U is corresponded in construction vector space(k)Another point P2, So that P2Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent.
Step 4):U is corrected using optimizing(k)(t), the point after being correctedIt is denoted as point P3, with seasonSo that P3Corresponding target function value J [u(k)(t)] than J [u(k-1)(t)] it is more excellent;
Step 5):If the target function value J [u of current iteration(k)(t)] with the target function value J [u of last iteration(k-1) (t)] difference of absolute value is less than precision tol, then judges convergence sexual satisfaction, the control strategy u that current iteration is obtained(k)(t) it is defeated Go out to control strategy output module 25;If convergence is unsatisfactory for, iterations k increases by 1, by u(k)(t) initial value is arranged to, Continue to execute step 2).
CN201711116197.5A 2017-11-13 2017-11-13 Hypersonic aircraft reentry section track optimization controller based on orthogonal configuration optimization Expired - Fee Related CN107908109B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201711116197.5A CN107908109B (en) 2017-11-13 2017-11-13 Hypersonic aircraft reentry section track optimization controller based on orthogonal configuration optimization

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201711116197.5A CN107908109B (en) 2017-11-13 2017-11-13 Hypersonic aircraft reentry section track optimization controller based on orthogonal configuration optimization

Publications (2)

Publication Number Publication Date
CN107908109A true CN107908109A (en) 2018-04-13
CN107908109B CN107908109B (en) 2020-02-28

Family

ID=61845212

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201711116197.5A Expired - Fee Related CN107908109B (en) 2017-11-13 2017-11-13 Hypersonic aircraft reentry section track optimization controller based on orthogonal configuration optimization

Country Status (1)

Country Link
CN (1) CN107908109B (en)

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108717588A (en) * 2018-06-07 2018-10-30 哈尔滨工业大学 A kind of track optimizing Initialization Algorithms based on Orthogonal Experiment and Design
CN109375649A (en) * 2018-12-19 2019-02-22 中国商用飞机有限责任公司 For controlling the method and system of aircraft
CN110020488A (en) * 2019-04-12 2019-07-16 中南大学 A kind of track method for customizing of curve trajectory SMART BULLET
CN110727285A (en) * 2019-11-27 2020-01-24 浙江大学 Gauss time distribution point control parameterization-based unpowered aviation aircraft control signal generation device and method
CN111026140A (en) * 2019-11-21 2020-04-17 浙江大学 Constraint full-process satisfied hypersonic aircraft trajectory optimization self-adaptive optimal controller
CN111045447A (en) * 2019-11-21 2020-04-21 浙江大学 High-precision hypersonic aircraft trajectory optimization multi-scale optimal control system
CN111061294A (en) * 2019-11-21 2020-04-24 浙江大学 Trajectory optimization self-adaptive optimal control system for nonstationary hypersonic aircraft
CN111103795A (en) * 2019-11-21 2020-05-05 浙江大学 Hypersonic aircraft reentry section track optimization controller based on intelligent self-adaptive optimization algorithm
CN111123700A (en) * 2019-11-21 2020-05-08 浙江大学 Constraint full-course satisfied optimal control system for obstacle-detouring flight of hypersonic aircraft
CN111123960A (en) * 2019-11-21 2020-05-08 浙江大学 Ultra-high precision hypersonic aircraft trajectory optimization optimal control instrument
CN111290436A (en) * 2020-03-16 2020-06-16 北京机电工程研究所 Aircraft wireless instruction correction method and system
CN111324035A (en) * 2019-11-21 2020-06-23 浙江大学 Adaptive optimal controller for trajectory optimization of hypersonic aircraft
CN111338364A (en) * 2019-11-21 2020-06-26 浙江大学 High-precision controller for optimizing trajectory of hypersonic aerocraft with quick response
CN113705117A (en) * 2021-05-25 2021-11-26 中国航空工业集团公司沈阳飞机设计研究所 Optimized analysis method for flight performance of hypersonic cruise aircraft
CN114488788A (en) * 2021-11-30 2022-05-13 浙江大学 Probability self-adaptive pollination optimized hypersonic aircraft reentry segment controller

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070038335A1 (en) * 2005-07-22 2007-02-15 Mcintyre Timothy J Real Power Regulation for the Utility Power Grid Via Responsive Loads
CN101464664A (en) * 2009-01-09 2009-06-24 浙江工业大学 Batch reactor optimal control method based on single population and pre-crossed differential evolution algorithm
CN101763086A (en) * 2009-12-29 2010-06-30 浙江大学 High-efficiency system and method for dynamic optimization of industrial process
CN101763083A (en) * 2009-12-29 2010-06-30 浙江大学 An effective industrial process dynamic optimization system and method capable of controlling variable parameterization
CN103273913A (en) * 2013-06-08 2013-09-04 浙江大学 Automobile automatic braking device based on orthogonal configuration optimization
CN103309234A (en) * 2013-06-08 2013-09-18 浙江大学 Orthogonal collocation optimization based batch reactor control system
CN103324086A (en) * 2013-06-08 2013-09-25 浙江大学 Batch reactor control system based on accurate punishment optimization
CN103303299B (en) * 2013-06-08 2015-07-22 浙江大学 Emergency braking signal generation device for high-speed train based on orthogonal collocation optimization

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070038335A1 (en) * 2005-07-22 2007-02-15 Mcintyre Timothy J Real Power Regulation for the Utility Power Grid Via Responsive Loads
CN101464664A (en) * 2009-01-09 2009-06-24 浙江工业大学 Batch reactor optimal control method based on single population and pre-crossed differential evolution algorithm
CN101763086A (en) * 2009-12-29 2010-06-30 浙江大学 High-efficiency system and method for dynamic optimization of industrial process
CN101763083A (en) * 2009-12-29 2010-06-30 浙江大学 An effective industrial process dynamic optimization system and method capable of controlling variable parameterization
CN103273913A (en) * 2013-06-08 2013-09-04 浙江大学 Automobile automatic braking device based on orthogonal configuration optimization
CN103309234A (en) * 2013-06-08 2013-09-18 浙江大学 Orthogonal collocation optimization based batch reactor control system
CN103324086A (en) * 2013-06-08 2013-09-25 浙江大学 Batch reactor control system based on accurate punishment optimization
CN103303299B (en) * 2013-06-08 2015-07-22 浙江大学 Emergency braking signal generation device for high-speed train based on orthogonal collocation optimization

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
胡云卿: "基于控制变量参数化的带约束最优控制问题计算方法", 《中国博士学位论文全文数据库信息科技辑》 *

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108717588A (en) * 2018-06-07 2018-10-30 哈尔滨工业大学 A kind of track optimizing Initialization Algorithms based on Orthogonal Experiment and Design
CN109375649A (en) * 2018-12-19 2019-02-22 中国商用飞机有限责任公司 For controlling the method and system of aircraft
CN109375649B (en) * 2018-12-19 2021-11-19 中国商用飞机有限责任公司 Method and system for controlling an aircraft
CN110020488A (en) * 2019-04-12 2019-07-16 中南大学 A kind of track method for customizing of curve trajectory SMART BULLET
CN111045447A (en) * 2019-11-21 2020-04-21 浙江大学 High-precision hypersonic aircraft trajectory optimization multi-scale optimal control system
CN111061294B (en) * 2019-11-21 2021-04-09 浙江大学 Trajectory optimization self-adaptive optimal control system for nonstationary hypersonic aircraft
CN111061294A (en) * 2019-11-21 2020-04-24 浙江大学 Trajectory optimization self-adaptive optimal control system for nonstationary hypersonic aircraft
CN111103795A (en) * 2019-11-21 2020-05-05 浙江大学 Hypersonic aircraft reentry section track optimization controller based on intelligent self-adaptive optimization algorithm
CN111123700A (en) * 2019-11-21 2020-05-08 浙江大学 Constraint full-course satisfied optimal control system for obstacle-detouring flight of hypersonic aircraft
CN111123960A (en) * 2019-11-21 2020-05-08 浙江大学 Ultra-high precision hypersonic aircraft trajectory optimization optimal control instrument
CN111045447B (en) * 2019-11-21 2023-08-29 浙江大学 High-precision hypersonic aircraft track optimization multi-scale optimal control system
CN111324035A (en) * 2019-11-21 2020-06-23 浙江大学 Adaptive optimal controller for trajectory optimization of hypersonic aircraft
CN111338364A (en) * 2019-11-21 2020-06-26 浙江大学 High-precision controller for optimizing trajectory of hypersonic aerocraft with quick response
CN111026140A (en) * 2019-11-21 2020-04-17 浙江大学 Constraint full-process satisfied hypersonic aircraft trajectory optimization self-adaptive optimal controller
CN111103795B (en) * 2019-11-21 2021-07-13 浙江大学 Hypersonic aircraft reentry section track optimization controller based on intelligent self-adaptive optimization algorithm
CN110727285A (en) * 2019-11-27 2020-01-24 浙江大学 Gauss time distribution point control parameterization-based unpowered aviation aircraft control signal generation device and method
CN111290436B (en) * 2020-03-16 2023-04-07 北京机电工程研究所 Aircraft wireless instruction correction method and system
CN111290436A (en) * 2020-03-16 2020-06-16 北京机电工程研究所 Aircraft wireless instruction correction method and system
CN113705117A (en) * 2021-05-25 2021-11-26 中国航空工业集团公司沈阳飞机设计研究所 Optimized analysis method for flight performance of hypersonic cruise aircraft
CN113705117B (en) * 2021-05-25 2022-09-20 中国航空工业集团公司沈阳飞机设计研究所 Optimized analysis method for flight performance of hypersonic cruise aircraft
CN114488788A (en) * 2021-11-30 2022-05-13 浙江大学 Probability self-adaptive pollination optimized hypersonic aircraft reentry segment controller

Also Published As

Publication number Publication date
CN107908109B (en) 2020-02-28

Similar Documents

Publication Publication Date Title
CN107908109A (en) A kind of hypersonic aircraft reentry stage track optimizing controller based on orthogonal configuration optimization
CN109725644A (en) A kind of hypersonic aircraft linear optimization control method
CN111103795B (en) Hypersonic aircraft reentry section track optimization controller based on intelligent self-adaptive optimization algorithm
CN105629734A (en) Trajectory tracking control method for NSV (Near Space Vehicle)
CN107065897B (en) Three-degree-of-freedom helicopter explicit model prediction control method
CN104597911A (en) Adaptive optimal butt joint trajectory tracking flying control method for air refueling receiving machine
CN109808853A (en) A kind of unmanned boat bow is to speed of a ship or plane multi-level control system and its control method
CN107885082A (en) A kind of Lunar satellite orbit tracking controller based on orthogonal configuration optimization
CN111045447B (en) High-precision hypersonic aircraft track optimization multi-scale optimal control system
An et al. Adaptive controller design for a switched model of air-breathing hypersonic vehicles
CN111123700B (en) Constraint full-course satisfied optimal control system for obstacle-detouring flight of hypersonic aircraft
CN111324035A (en) Adaptive optimal controller for trajectory optimization of hypersonic aircraft
CN115129072A (en) Terminal sliding mode control method under position tracking deviation constraint of fixed wing unmanned aerial vehicle
CN109062242A (en) A kind of new rotor wing unmanned aerial vehicle control method
CN113885543A (en) Design method of navigation body auto-disturbance rejection roll controller under complex sea condition disturbance
CN108845508B (en) CMAC-sliding mode integrated control-based semi-physical simulation control method for unmanned aerial vehicle
CN111061294B (en) Trajectory optimization self-adaptive optimal control system for nonstationary hypersonic aircraft
Li et al. Novel fuzzy approximation control scheme for flexible air-breathing hypersonic vehicles with non-affine dynamics and amplitude and rate constraints
Zhou et al. Parameter Optimization on FNN/PID compound controller for a three-axis inertially stabilized platform for aerial remote sensing applications
CN114610055A (en) Aircraft control method and aircraft
CN114355770A (en) Hypersonic aircraft reentry segment controller for optimizing invasive weed population distribution
Kada Design of flight control systems for a hypersonic aircraft using sliding-pid control
CN111026140B (en) Constraint full-process satisfied hypersonic aircraft trajectory optimization self-adaptive optimal controller
CN111338364B (en) High-precision controller for optimizing trajectory of hypersonic aerocraft with quick response
Garcia et al. Adaptive and resilient flight control system for a small unmanned aerial system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20200228

Termination date: 20211113

CF01 Termination of patent right due to non-payment of annual fee