CN105938370B - The control system and its modeling and simulating method of morphing aircraft collaboration flight - Google Patents
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Abstract
The invention discloses the control systems and its modeling and simulating method of a kind of collaboration flight of morphing aircraft, and the system comprises flight controllers, global deformation controller, network-bus, local deformation controller, distributed sensor, distribution driver, distressed structure, sensor.The deformation collaboration that the present invention illustrates morphing aircraft by emulation and can complete well across height, across speed is flown, demonstrate the reasonability and superiority of proposed control strategy, and the Beneficial Effect for showing the deformation of morphing aircraft energy synergetic structure improves maneuvering flight performance, expand flight envelope, embodies advantage of the morphing aircraft compared to conventional aircraft.
Description
Technical field
The present invention relates to morphing aircraft control fields, more particularly to a kind of control system of morphing aircraft collaboration flight
System and its modeling and simulating method.
Background technique
Dual-use aviation in recent years proposes increasingly higher demands to aircraft performance, and aircraft should adapt to fly
The variation of row environment executes different task, guarantees flying quality again, and also to meet cost-effectiveness requirement, and current flies
Row device technology can not meet these requirements simultaneously.Morphing aircraft technology is that one kind is potential, can effectively solve the problems, such as this
Technological approaches.Morphing aircraft is that one kind can be winged with the aviation for changing aerodynamic configuration and then realization multitask flight of large scale
Row device.The research of morphing aircraft has a long history, and early in 1916, the U.S. was it has been suggested that " Variable Geometry Wing "
Patent application.In recent years, the fast development in the fields such as new material, new driving device and new control technology further excites people
The enthusiasm of intelligent morphing aircraft is studied, in the past few decades, countries in the world have been carried out greatly in morphing aircraft technology
Quantifier elimination.
Under different flying conditions, in order to obtain optimal performance, morphing aircraft needs change in sizable range
Become aerodynamic configuration, it is thus impossible to Dynamic Modeling is carried out using morphing aircraft as single rigid body as conventional aircraft, and
Establish a kind of kinetic model comprising distressed structure.
Currently, classical Newton mechanics method is mostly used greatly, aircraft when carrying out Dynamic Modeling to morphing aircraft
Regard an entirety as, seek its momentum and its moment of momentum to mass center, then to time derivation, and then establishes aircraft and close outside
Translational motion under power F effect and the rotational motion equation under outer resultant moment M effect.In the process, it is contemplated that aircraft
Deformation, need by integral seek statical moment of the entire aircraft about reference point, while need to rotary inertia derivation with
It solves the problems, such as aircraft deformation bring rotary inertia variation, it can be found that this method calculation amount is larger, and needs to winged
The shape and Mass Distribution of row device are accurately modeled.In addition, when carrying out dynamic analysis to morphing aircraft, at present very
Hardly possible analysis is in addition to air force variation, influence of the inertia to vehicle dynamics characteristic caused by being moved by variant.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of control system of morphing aircraft collaboration flight and its build
Mould emulation mode can improve maneuvering flight performance, expand flight envelope.
The present invention is to solve above-mentioned technical problem by following technical proposals: a kind of morphing aircraft deformation collaboration is winged
Row control system comprising:
Flight controller realizes flight control for controlling the state of flight of aircraft；
Global deformation controller, is connected with flight controller, controls distressed structure；
Network-bus, the channel for connecting local deformation controller and distributed sensor, as data communication；
Local deformation controller, is connected with distributed sensor, for controlling distressed structure；
Distributed sensor is connected with local deformation controller, distribution driver, the hardware configuration as control system；
Distribution driver, for driving distressed structure；
Distressed structure makes morphing aircraft realize the mechanical structure of variant, and aircraft is made to obtain high pneumatic efficiency；
Sensor detects the state of distressed structure and information is fed back winged deformation controller.
The present invention also provides the modeling and simulating methods that a kind of morphing aircraft deforms collaboration flight control system comprising with
Lower step:
Step 1 has selected several operating points in morphing aircraft flight envelope, has worked out corresponding fuzzy rule；
Step 2 establishes whole envelope longitudinal direction T-S fuzzy model, to describe former nonlinear kinetics mould by linear model
Type；
Step 3 is based on T-S fuzzy model, in conjunction with robust H afterwards∞Control thought and PDC principle, propose based on continuous T-
The Fuzzy Robust Controller H of S fuzzy model∞Control strategy；
Step 4 calculates fuzzy gain matrix by limited LMI condition, ensure that the Existence of Global Stable of deformation flight course
And robust performance, and the target flight state of energy asymptotic tracking reference signal；
Step 5 drops the continuous T-S fuzzy model discretization of morphing aircraft using Fuzzy Lyapunov functions method
Low conservative proposes the DFRHC strategy based on Discrete T-S fuzzy model, passes through limited LMI item in conjunction with Non-PDC principle
Part calculates more feasible discrete-time fuzzy gain matrix, better assure that the Existence of Global Stable of deformation flight course, robust performance and
Tracking accuracy；
Designed controller is introduced morphing aircraft non-linear dynamic model, passes through numerical simulation exhibition by step 6
Show.
Preferably, the step 2 the following steps are included:
Step 2 11 establishes the T-S fuzzy model of nonlinear system:
In formula, ηj(t), j=1,2 ..., g are former piece variable；For j-th of former piece variable η in the i-th rulej(t) right
The fuzzy subset answered；Ai, BiFor the local linear sytem matrix of the i-th rule.For specific nonlinear system, former piece
The selection of variable, the division of fuzzy subset, quantity of fuzzy rule etc. depend on the target of system self-characteristic and control design case；
Step 2 12 establishes the Local Linear Model of nonlinear system:
In formula,For state vector；For input vector；For output vector；For nonlinear system function, f (x (t))=[f1(x(t)) f2(x(t)) … fn(x(t))]T。
Preferably, the step 3 includes the Fuzzy Robust Controller H based on T-S fuzzy system∞The design of control program, to not true
Determine the Fuzzy Robust Controller H of the track reference signal of T-S Design of Fuzzy Systems∞Control strategy specific structure are as follows:
In formula, fuzzy gain matrixFor the constant value matrix of corresponding dimension, KiFor
The fuzzy gain matrix of i-th rule,For controllable output vector；uf(t)
For fuzzy-feedforward control part, it is therefore an objective to provide baseline stability according to tracking target；ubIt (t) is fuzzy feedback-control part, mesh
Be guarantee closed-loop system robust stability.
Preferably, the step 5 the following steps are included:
Step 5 11, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞The design of control program, to uncertain
Continuous T-S obscures augmented system and carries out discretization, uncertain Discrete T-S fuzzy augmented system is obtained, using fuzzy Lyapunov
Functional based method reduces conservative, in conjunction with Non-PDC principle, proposes a kind of new DFRHC strategy, specific design structure are as follows:
In formula, Fi, Gi, i=1,2 ... r are the constant value matrix of corresponding dimension.
Step 5 12, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞Control program substitution does not know discrete
T-S obscures augmented system, obtains closed-loop system:
For not knowing Discrete T-S fuzzy closed-loop system, constant γ > 0 is given, if there is symmetric positive definite real matrixMeet:
In formula, * indicates the correspondence transposition element of coherent element in symmetrical matrix, then closed-loop system asymptotically stable in the large and tool
There is H∞Performance indicator γ.
For not knowing Discrete T-S fuzzy augmented system, constant γ > 0 is given, there are DFRHC, so that closed-loop system is complete
Office Asymptotic Stability and have H∞The adequate condition of performance indicator γ is that there are real matrixesMeet following LMI conditions:
In formula
The positive effect of the present invention is that: by emulation illustrate morphing aircraft can complete well across height,
Deformation across speed cooperates with flight, demonstrates the reasonability and superiority of proposed control strategy, and show morphing aircraft energy
The Beneficial Effect of synergetic structure deformation improves maneuvering flight performance, expands flight envelope, embodies morphing aircraft and compare
In the advantage of conventional aircraft.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of morphing aircraft of the present invention deformation collaboration flight control system.
Fig. 2 is the simulation comparison result figure of flying speed curve of the present invention.
Fig. 3 is the simulation comparison result figure of angle of attack curve of the present invention.
Fig. 4 is the simulation comparison result figure of pitching angular curve of the present invention.
Fig. 5 is the simulation comparison result figure of rate of pitch curve of the present invention.
Fig. 6 is the simulation comparison result figure of flying height curve of the present invention.
Specific embodiment
Present pre-ferred embodiments are provided with reference to the accompanying drawing, in order to explain the technical scheme of the invention in detail.
As shown in Figure 1, morphing aircraft deformation collaboration flight control system of the present invention includes flight controller, global deformation
Controller, network-bus, local deformation controller, distributed sensor, distribution driver, distressed structure, sensor,
In:
Flight controller realizes flight control for controlling the state of flight of aircraft；
Global deformation controller, is connected with flight controller, controls distressed structure；
Network-bus, for connecting local deformation controller and distributed sensor, channel as data communication:
Local deformation controller, is connected with distributed sensor, for controlling distressed structure；
Distributed sensor is connected with local deformation controller, distribution driver, the hardware configuration as control system；
Distribution driver, for driving distressed structure；
Distressed structure makes morphing aircraft realize the mechanical structure of variant, and aircraft is made to obtain high pneumatic efficiency；
Sensor detects the state of distressed structure and information is fed back winged deformation controller.
The modeling and simulating method of morphing aircraft of the present invention deformation collaboration flight control system the following steps are included:
Step 1 has selected several operating points in morphing aircraft flight envelope, has worked out corresponding fuzzy rule；
Step 2 establishes whole envelope longitudinal direction T-S fuzzy model, to describe former nonlinear kinetics mould by linear model
Type；
Step 3 is based on T-S fuzzy model, in conjunction with robust H afterwards∞Control thought and PDC principle, propose based on continuous T-
The Fuzzy Robust Controller H of S fuzzy model∞Control strategy；
Step 4 calculates fuzzy gain matrix by limited LMI condition, ensure that the Existence of Global Stable of deformation flight course
And robust performance, and the target flight state of energy asymptotic tracking reference signal；
Step 5 drops the continuous T-S fuzzy model discretization of morphing aircraft using Fuzzy Lyapunov functions method
Low conservative proposes the DFRHC strategy based on Discrete T-S fuzzy model, passes through limited LMI item in conjunction with Non-PDC principle
Part calculates more feasible discrete-time fuzzy gain matrix, better assure that the Existence of Global Stable of deformation flight course, robust performance and
Tracking accuracy；
Designed controller is introduced morphing aircraft non-linear dynamic model, passes through numerical simulation exhibition by step 6
Show.
Wherein, the step 2 the following steps are included:
Step 2 11, the T-S fuzzy model formula of nonlinear system such as following formula (1):
In formula, ηj(t), j=1,2 ..., g are former piece variable；For j-th of former piece variable η in the i-th rulej(t) right
The fuzzy subset answered；Ai, BiFor the local linear sytem matrix of the i-th rule.For specific nonlinear system, former piece
The selection of variable, the division of fuzzy subset, quantity of fuzzy rule etc. depend on the target of system self-characteristic and control design case；
Step 2 12, the formula of the Local Linear Model of nonlinear system such as following formula (2):
In formula,For state vector；For input vector；For output vector；For nonlinear system function, f (x (t))=[f1(x(t)) f2(x(t)) … fn(x(t))]T。
The step 3 includes: the Fuzzy Robust Controller H based on T-S fuzzy system∞The design of control program, to uncertain T-S
The Fuzzy Robust Controller H of the track reference signal of Design of Fuzzy Systems∞Control strategy specific structure such as formula (3):
In formula, fuzzy gain matrixFor the constant value matrix of corresponding dimension, KiFor
The fuzzy gain matrix of i-th rule,For controllable output vector；uf(t)
For fuzzy-feedforward control part, it is therefore an objective to provide baseline stability according to tracking target；ubIt (t) is fuzzy feedback-control part, mesh
Be guarantee closed-loop system robust stability.
The step 5 the following steps are included:
Step 5 11, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞The design of control program, to uncertain
Continuous T-S obscures augmented system and carries out discretization, uncertain Discrete T-S fuzzy augmented system is obtained, using fuzzy Lyapunov
Functional based method reduces conservative, in conjunction with Non-PDC principle, proposes a kind of new DFRHC strategy, specific design structure such as formula
(4):
In formula, Fi, Gi, i=1,2 ... r are the constant value matrix of corresponding dimension.
Step 5 12, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞Control program substitution does not know discrete
T-S obscures augmented system, obtains closed-loop system formula (5):
For not knowing Discrete T-S fuzzy closed-loop system, constant γ > 0 is given, if there is symmetric positive definite real matrix Pi
=Pi T> 0, i=1,2 ..., r meet formula (6)
In formula, * indicates the correspondence transposition element of coherent element in symmetrical matrix, then closed-loop system asymptotically stable in the large and tool
There is H∞Performance indicator γ.
For not knowing Discrete T-S fuzzy augmented system, constant γ > 0 is given, there are DFRHC, so that closed-loop system is complete
Office Asymptotic Stability and have H∞The adequate condition of performance indicator γ is that there are real matrixesMeet following LMI conditionals (7)
In formula
As shown in Fig. 2 to 6, in the wing contraction process that joined composite interference, three kinds of controllers fly variant
Flying speed and altitude when row device has returned to initial after wing deformation, but only RGSC/SMDO can be very well steady
Determine whole deformation flight course, remain the constant of flying speed and altitude, almost without any fluctuation, controls precision
It is high；OC and GSC then produces biggish deviation process, while being constantly in oscillatory regime.This shows that conventional OC and GSC is lacked
The weary rejection ability to composite interference, and RGSC/SMDO is then guaranteeing that system is complete by the observation compensation control to composite interference
High robust performance is additionally provided except office's stability.
Particular embodiments described above, the technical issues of to solution of the invention, technical scheme and beneficial effects carry out
It is further described, it should be understood that the above is only a specific embodiment of the present invention, is not limited to
The present invention, all within the spirits and principles of the present invention, any modification, equivalent substitution, improvement and etc. done should be included in this
Within the protection scope of invention.
Claims (4)
1. a kind of modeling and simulating method of morphing aircraft deformation collaboration flight control system, morphing aircraft deformation collaboration flight
Control system includes:
Flight controller realizes flight control for controlling the state of flight of aircraft；
Global deformation controller, is connected with flight controller, controls distressed structure；
Network-bus, the channel for connecting local deformation controller and distributed sensor, as data communication；
Local deformation controller, is connected with distributed sensor, for controlling distressed structure；
Distributed sensor is connected with local deformation controller, distribution driver, the hardware configuration as control system；
Distribution driver, for driving distressed structure；
Distressed structure makes morphing aircraft realize the mechanical structure of variant, and aircraft is made to obtain high pneumatic efficiency；
Sensor detects the state of distressed structure and information is fed back winged deformation controller；
It is characterized in that, itself the following steps are included:
Step 1 has selected several operating points in morphing aircraft flight envelope, has worked out corresponding fuzzy rule；
Step 2 establishes whole envelope longitudinal direction T-S fuzzy model, to describe former non-linear dynamic model by linear model；
Step 3 is based on T-S fuzzy model, in conjunction with robust H afterwards∞Control thought and PDC principle are proposed based on continuous T-S mould
The Fuzzy Robust Controller H of fuzzy model∞Control strategy；
Step 4 calculates fuzzy gain matrix by limited LMI condition, ensure that Existence of Global Stable and the Shandong of deformation flight course
Stick performance, and the target flight state of energy asymptotic tracking reference signal；
Continuous T-S fuzzy model the discretization of morphing aircraft is reduced using Fuzzy Lyapunov functions method and is protected by step 5
Keeping property proposes the DFRHC strategy based on Discrete T-S fuzzy model, passes through limited LMI condition meter in conjunction with Non-PDC principle
More feasible discrete-time fuzzy gain matrix is calculated, better assures that Existence of Global Stable, robust performance and the tracking of deformation flight course
Precision；
Designed controller is introduced morphing aircraft non-linear dynamic model, is shown by numerical simulation by step 6.
2. the modeling and simulating method of morphing aircraft deformation collaboration flight control system as described in claim 1, feature exist
In, the step 2 the following steps are included:
Step 2 11 establishes the T-S fuzzy model of nonlinear system:
In formula, ηj(t), j=1,2 ..., g are former piece variable；For j-th of former piece variable η in the i-th rulej(t) corresponding mould
Paste subset；Ai, BiFor the local linear sytem matrix of the i-th rule；For specific nonlinear system, former piece variable
Selection, the division of fuzzy subset, quantity of fuzzy rule etc. depend on the target of system self-characteristic and control design case；
Step 2 12 establishes the Local Linear Model of nonlinear system:
In formula,For state vector；For input vector；For output vector；For nonlinear system function, f (x (t))=[f1(x(t)) f2(x(t)) … fn(x(t))]T。
3. the modeling and simulating method of morphing aircraft deformation collaboration flight control system as described in claim 1, feature exist
In the step 3 includes the Fuzzy Robust Controller H based on T-S fuzzy system∞The design of control program, to the fuzzy system of uncertain T-S
The Fuzzy Robust Controller H of the track reference signal for design of uniting∞Control strategy specific structure are as follows:
In formula, fuzzy gain matrixFor the constant value matrix of corresponding dimension, KiIt is i-th
The fuzzy gain matrix of rule,For controllable output vector；ufIt (t) is fuzzy
Feed-forward control portion, it is therefore an objective to provide baseline stability according to tracking target；ubIt (t) is fuzzy feedback-control part, it is therefore an objective to protect
Demonstrate,prove the robust stability of closed-loop system.
4. the modeling and simulating method of morphing aircraft deformation collaboration flight control system as described in claim 1, feature exist
In, the step 5 the following steps are included:
Step 5 11, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞The design of control program, to uncertain continuous
T-S obscures augmented system and carries out discretization, uncertain Discrete T-S fuzzy augmented system is obtained, using Fuzzy Lyapunov functions
Method reduces conservative, in conjunction with Non-PDC principle, proposes a kind of new DFRHC strategy, specific design structure are as follows:
In formula, Fi, Gi, i=1,2 ... r are the constant value matrix of corresponding dimension；
Step 5 12, the discrete-time fuzzy robust H based on discrete T-S fuzzy system∞Control program substitution does not know discrete T-S mould
Augmented system is pasted, closed-loop system is obtained:
For not knowing Discrete T-S fuzzy closed-loop system, constant γ > 0 is given, if there is symmetric positive definite real matrix Pi=Pi T
> 0, i=1,2 ..., r meet:
In formula, * indicate symmetrical matrix in coherent element correspondence transposition element, then closed-loop system asymptotically stable in the large and have H∞
Performance indicator γ；
For not knowing Discrete T-S fuzzy augmented system, constant γ > 0 is given, there are DFRHC, so that the closed-loop system overall situation is gradually
It is close to stablize and there is H∞The adequate condition of performance indicator γ is that there are real matrixesMeet following LMI conditions:
In formula
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