CN112363393A - Model-free self-adaptive preset performance control method for unmanned ship power positioning - Google Patents

Model-free self-adaptive preset performance control method for unmanned ship power positioning Download PDF

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CN112363393A
CN112363393A CN202011158507.1A CN202011158507A CN112363393A CN 112363393 A CN112363393 A CN 112363393A CN 202011158507 A CN202011158507 A CN 202011158507A CN 112363393 A CN112363393 A CN 112363393A
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向先波
李锦江
袁烨
张琴
杨少龙
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Huazhong University of Science and Technology
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Abstract

The invention provides a model-free self-adaptive preset performance control method for unmanned ship dynamic positioning. Firstly, a novel preset performance function is provided, and a foundation is laid for the conversion of a preset performance error; and then, the dynamic positioning system with limited error performance is converted into a system with non-limited error performance based on the proposed preset performance function, and a controller designed based on the conversion system can ensure that the closed-loop signals of the system are consistent and finally bounded and the transient performance of the system can be guaranteed. And finally, developing the design of the controller based on an instruction filtering backstepping method, and introducing a self-adaptive method to obtain the model-free self-adaptive preset performance controller. The designed controller gets rid of the requirement of accurate modeling of the hydrodynamic force and the additional mass items of the unmanned ship and can realize the control of the preset performance of the unmanned ship under the external time-varying disturbance and input saturation constraint.

Description

Model-free self-adaptive preset performance control method for unmanned ship power positioning
Technical Field
The invention relates to the technical field of unmanned ship control, in particular to a model-free self-adaptive preset performance control method for power positioning of an unmanned ship (comprising an underwater navigation body, an underwater robot, an unmanned ship on the water and the like).
Background
In recent years, with the depletion of land fuel resources, the strategic position of oceans occupying about 71% of the area of the earth has been increasing. The development of marine equipment technology is indispensable for the sufficient exploration and exploitation of marine resources. The marine intelligent equipment represented by unmanned boats (including underwater navigation bodies, underwater robots, unmanned ships on water and the like) is a main carrier for marine operation at the present stage, and the traditional mooring/anchoring positioning cannot meet the positioning requirement of the marine intelligent equipment operation due to the limitation of the lengths of mooring lines and anchor chains. The dynamic positioning is a positioning method which can automatically keep the position by depending on the dynamic propulsion, the auxiliary of a mooring/anchoring system is not needed in the working process, the limit of the working water depth is eliminated, the interference of ocean waves and sea wind can be resisted, and the relatively accurate dynamic positioning of the unmanned ship is ensured.
A series of advanced control methods such as inversion control, sliding mode control and fuzzy control are applied to the design of a power positioning controller of the unmanned ship, but the traditional controller design can only ensure that the unmanned ship can be converged to an expected position and heading at last, and transient performance in the power positioning process cannot be considered. The design of the preset performance control method considering the transient performance in the dynamic positioning process is worthy of deep research.
Disclosure of Invention
The invention aims to solve the problem of model-free adaptive preset performance control of the power positioning of the unmanned ship under the constraints of external time-varying disturbance and actuator input saturation.
In order to achieve the purpose, a preset performance function is introduced firstly, the unmanned ship dynamic system with limited error performance is converted into a new system with unlimited error performance, and the unmanned ship dynamic positioning requirement can be met only by designing a controller to enable the system to finally converge on an expected signal, and meanwhile the transient performance of the system can be guaranteed. And then, designing the controller based on a reverse step design method, and recurrently obtaining a virtual intermediate control variable. In order to avoid complex differential operation, an instruction filter is introduced to convert the differential operation into simple algebraic operation. And in consideration of instruction filtering errors caused by the introduction of an instruction filter, constructing an error compensation auxiliary system for processing. And designing a robust item for stabilization aiming at external time-varying disturbance. And realizing model self-adaptation based on the self-adaptation technology. And finally, obtaining unsaturated control output through the constructed auxiliary dynamic system when solving the control force/moment, thereby realizing model-free adaptive preset performance control of the unmanned ship under the external time-varying disturbance and input saturation constraint.
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FIG. 1 is a general control block diagram of the fuzzy adaptive default performance control method for unmanned ship dynamic positioning in the invention.
Fig. 2 is a supplement to fig. 1, and shows in detail the command filtering process of the robust adaptive controller design in the fuzzy adaptive preset performance control method for unmanned ship dynamic positioning.
Fig. 3 is a dynamic positioning unmanned boat speed time-course curve.
Figure 4 is a graph of dynamically positioned drones level position and heading duration.
Fig. 5 is a dynamic positioning unmanned boat actuator output thrust/torque time curve.
FIG. 6 is a dynamic positioning unmanned boat transfer position error surface vector time curve.
FIG. 7 is a dynamic positioning unmanned boat velocity error surface vector duration plot.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The method comprises the following steps: based on the novel preset performance function, the dynamic positioning system with limited error performance is converted into a new system with unlimited error performance, and a foundation is laid for backstepping design.
The specific implementation process is as follows
The three-degree-of-freedom mathematical model of the dynamic positioning unmanned ship in the horizontal plane considering the dynamic state of the propeller can be expressed as follows
Figure BDA0002743581370000031
Wherein D is a damping matrix, M is a mass matrix of the unmanned ship,
Figure BDA0002743581370000032
the external time-varying disturbance caused by wind, wave and flow,
Figure BDA0002743581370000033
thrust and moment provided for unmanned boat propulsion systems, AtrIs a dynamic matrix of the thrusters of the system,
Figure BDA0002743581370000034
obtaining unsaturated thrust and torque for controller output, Δ τ ═ τp-τc，τpThe actual output signal obtained after the controller output torque is subjected to the following saturation amplitude limiting is specifically expressed as follows.
Figure BDA0002743581370000035
Defining a pose error vector e1＝x-xd,e2＝y-yd,
Figure BDA0002743581370000036
Based on the proposed novel error transfer function
Figure BDA0002743581370000037
Respectively representConversion errors of three degrees of freedom of surging, swaying and surging. Wherein the content of the first and second substances,
Figure BDA0002743581370000038
Figure BDA0002743581370000039
eirepresenting the longitudinal position error, the transverse position error and the heading error of the unmanned ship, ei,l and ei,uRespectively representing the lower limit and the upper limit, epsilon, of the preset performance error range in each degree of freedomiIs the new error variable after conversion. This preset performance error transfer function has the following important properties:
1) when e isi→-ei,lWhen is equal toi→ infinity. When e isi→ei,uWhen is equal toi→∞
2) If and only if eiWhen equal to 0, epsiloni＝0
Wherein the boundary limiting function is defined as follows
Figure BDA00027435813700000310
Where ρ (t) ═ ρ (ρ)0-ρ∞)e-kt+ρ∞Is a positive function, p, which is strictly monotonically decreasing with respect to time t0、ρ∞、k、δi,l、δi,uAre all set normal numbers. The converted system is obtained after derivation
Figure BDA0002743581370000041
wherein ,
Figure BDA0002743581370000042
let epsilon equal to [ epsilon ]1,ε2,ε3]T，f＝[f1,f2,f3]T，g＝diag[g1,g2,g3]Can obtain the product
Figure BDA0002743581370000043
Step two: solving control law by adopting backstepping design method
The specific implementation process is as follows
The error variables in the backstepping design process are defined as follows
Figure BDA0002743581370000044
Selecting a first Lyapunov function
Figure BDA0002743581370000045
Derived by derivation
Figure BDA0002743581370000051
The following virtual control quantity is obtained through recursion
α1＝g-1(-K1z1-f)
wherein ,K1＝diag([K11,K12,K13]) A symmetric matrix is designed for positive definite.
To avoid a complicated derivation process, the following instruction filter is introduced
Figure BDA0002743581370000052
wherein ,ωn1Is that the natural frequency of the filter satisfies omegan1＞0，ζ1Is that the design constant satisfies ζ1∈(0,1]。
Figure BDA0002743581370000053
Is the filter output, [ phi ]12Is a filter state vector. The virtual control quantity is used as the filter input, and the output of the filter is obtained to replace the virtual control quantity. This method successfully converts complex differential operations into simple algebraic operation problems. To overcome the filtering error caused by the instruction filter, the filtering error is defined as delta1＝φ11-α1And constructing the following model-free error compensation auxiliary system
Figure BDA0002743581370000054
wherein ,ξ1、ξ2Is a state vector, ξ2As will be defined below. The error surface vector of the switching position after considering the filtering error can be redefined as
s1＝z1-ξ1
For the second error plane vector, the following Lyapunov function is defined
Figure BDA0002743581370000055
Derived therefrom to obtain
Figure BDA0002743581370000056
The following virtual control quantity is obtained through recursion
Figure BDA0002743581370000057
wherein ,τrobThe method is a robust item designed for composite errors caused by external time-varying disturbance. K2＝diag([K21,K22,K23]) Designing a symmetric matrix for positive definite, λ and l being positive definite design constants
Figure BDA0002743581370000058
And
Figure BDA0002743581370000061
is an adaptive model parameter, and the conversion of the matrix to vector form is as follows:
Figure BDA0002743581370000062
Figure BDA0002743581370000063
wherein ,mi and diRespectively, the column vectors representing the ith row elements of the inertia matrix and the damping matrix. Theta1 and Θ2The corresponding adaptive law is designed as follows
Figure BDA0002743581370000064
Figure BDA0002743581370000065
wherein ,KD、KM、ΓD、ΓMA positive diagonal matrix is determined for the design to be made.
And introducing a second instruction filter, taking the virtual control quantity as the input of the filter, and taking the output of the filter as the actual control quantity.
Figure BDA0002743581370000066
wherein ,ωn2Is that the natural frequency of the filter satisfies omegan2＞0，ζ2Is that the design constant satisfies ζ2∈(0,1]。
Figure BDA0002743581370000067
Is the filter output, [ phi ]22Is a filter state vector. Defining the filter error delta2＝φ21-α2The model-free error compensation auxiliary system is designed as
Figure BDA0002743581370000068
wherein ,ξ3∈R3Is a compensation vector, satisfies xi3(0)＝0 and
Figure BDA0002743581370000069
the velocity error surface vector after considering the filtering error can be redefined as
s2＝z2-ξ2
For the third error plane vector, the following Lyapunov function is defined
Figure BDA00027435813700000610
After substitution, the final control law can be obtained
Figure BDA0002743581370000071
wherein ,K3＝diag([K31,K32,K33]) and Kc＝diag([Kc1,Kc2,Kc3]) Designing a symmetric matrix for positive determination, and theta is an auxiliary dynamic system variable
Figure BDA0002743581370000072
wherein ,Kθ＝diag([Kθ1,Kθ2,Kθ3]) Is a positive definite design matrix.
The implementation case is as follows: in order to verify the effect of the control method in the invention, a certain unmanned ship model is used as a simulation object for developmentThe following simulation tests: initial position of unmanned ship
Figure BDA0002743581370000073
The desired position is [ u (0), v (0), r (0)]＝[0m/s,0m/s,0m/s]. External disturbance set to
τdx＝1+0.2m11d(t),τdy＝1+0.2m22d(t),τdpsi＝1+0.003m33d(t)
d(t)＝0.1sin(0.2t)
wherein ,m11、m22、m33Is an unmanned boat quality item. In the dynamic updating process, the inertia matrix of the system is made to be
M＝diag([5.3122×106+t×103,8.2831×106+t×103,3.7454×109+t×103])
To simulate the variable load process of an unmanned boat.
The simulation results are as follows, fig. 3 shows the speed history curve of the unmanned boat dynamic positioning, fig. 4 shows the horizontal plane position and heading angle history curve of the unmanned boat dynamic positioning, and fig. 5 shows the time history curve of the actuator output in the unmanned boat dynamic positioning. It can be seen that the unmanned surface vehicle can be converged to an expected pose finally, and the pose of the unmanned surface vehicle in the transient process is always under the constraint of the upper and lower boundaries of the preset performance function. Fig. 6 and 7 show the time history curves of the unmanned surface vehicle dynamic positioning switching position error plane vector and the speed error plane vector after considering the filtering error, and it can be seen that the error is close to 0 under the control of the designed controller.

Claims (9)

1. A model-free self-adaptive preset performance control method for unmanned ship dynamic positioning is characterized by comprising the following steps:
a novel preset performance error transfer function is provided;
a preset performance control idea is introduced, and a dynamic positioning system with limited error performance is converted into a new system with unlimited error performance;
carrying out controller backstepping design work by combining linearization feedback and robust adaptive technology to obtain a preliminary virtual intermediate variable;
filtering the virtual intermediate variable by using an instruction filter to avoid differential operation, and designing a corresponding model-free filtering error elimination auxiliary system to perform error compensation;
and the adaptive technology is adopted to carry out model adaptive updating, so that the controller effect under the variable load working condition is ensured.
2. The model-free adaptive predictive performance control method for unmanned surface vehicle dynamic positioning of claim 1, wherein a new predictive performance function is proposed as follows
Figure FDA0002743581360000011
wherein ,
Figure FDA0002743581360000012
eirespectively representing the longitudinal position error, the transverse position error and the heading error of the unmanned boat on the horizontal plane, ei,l and ei,uRespectively representing the lower limit and the upper limit, epsilon, of the preset performance error range in each degree of freedomiIs the new error variable after conversion.
3. The model-free adaptive preset performance control method for the power positioning of the unmanned ship as claimed in claim 1, wherein the preset performance control method is introduced based on a third order power positioning unmanned ship model, transient and steady state performance of the power positioning unmanned ship considering propeller dynamics is limited within the following preset upper and lower limits,
Figure FDA0002743581360000013
wherein ,ei,l(t) and ei,u(t) represents the performance upper and lower limits of three degrees of freedom, δi,l and δi,uIs a predetermined performance parameter, δi(t) is an exponential function of the decay.
4. The model-free adaptive preset performance control method for the unmanned ship dynamic positioning according to claim 1, characterized in that a preset performance control concept is introduced to convert a dynamic positioning system with limited error performance into a new system with unlimited error performance, and lay a foundation for backstepping design, so that a controller designed according to the method can restrict transient and steady performance of the system within a preset performance limit range, and the method is obtained by performing error conversion based on a novel preset performance function of claim two:
Figure FDA0002743581360000021
therefore, the system has the performance of unlimited error, the controller is designed to ensure that the system is stably equivalent to the control of the preset performance range of the claim III, the derivation and the matrix form are worked out to obtain the following new system with the performance of unlimited error, the foundation is laid for the backstepping design,
Figure FDA0002743581360000022
wherein f is a continuous function, g is a velocity gain, D is a damping matrix, M is a mass matrix of the unmanned ship,
Figure FDA0002743581360000023
the external time-varying disturbance caused by wind, wave and flow,
Figure FDA0002743581360000024
thrust and moment provided for unmanned boat propulsion systems, AtrIs a dynamic matrix of the thrusters of the system,
Figure FDA0002743581360000025
obtaining unsaturated thrust and torque for controller output, Δ τ ═ τp-τc，τpThe actual output signal is obtained after the controller output torque is subjected to the following saturation amplitude limiting.
5. The model adaptive preset performance control method for the dynamic positioning of the unmanned ship as claimed in claim 1, wherein the virtual intermediate control variables used in the backstepping design process are as follows:
α1＝g-1(-K1z1-f)
Figure FDA0002743581360000026
wherein ,K2Is a positive definite design diagonal matrix,
Figure FDA0002743581360000027
and
Figure FDA0002743581360000028
in order to adapt the parameters of the system model,
Figure FDA0002743581360000029
is the output of the instruction filter, s1Is a conversion position error, tau, taking into account a filtering errorrobIs a robust term designed for external time-varying disturbances.
6. The virtual intermediate control variable according to claim 5, wherein the calculation method for processing the robust term of the unmanned ship disturbed by wind and wave is as follows:
Figure FDA0002743581360000031
wherein ,s2To account for the velocity error surface vector after the command filter compensates for the error, l and λ are to be setNormal counts were counted.
7. The model-free adaptive predictive performance control method for unmanned surface vehicle dynamic positioning as claimed in claim 1, wherein the adaptive update law of the system model parameters M and D is
Figure FDA0002743581360000032
Figure FDA0002743581360000033
wherein ,KD、KM、ΓD、ΓMFor the positive definite diagonal matrix to be designed,
Figure FDA0002743581360000034
and
Figure FDA0002743581360000035
respectively representing the adaptive estimation vectors of the damping matrix and the inertia matrix.
8. The model-free adaptive preset performance control method for the unmanned ship dynamic positioning according to claim 1, wherein the model-free instruction filter designed for the virtual intermediate variable in the backstepping design process is as follows:
Figure FDA0002743581360000036
Figure FDA0002743581360000037
in view of the unavoidable filtering errors, the corresponding model-free filter compensation assistance system is designed as follows:
Figure FDA0002743581360000038
Figure FDA0002743581360000039
Figure FDA00027435813600000310
wherein ,K1 and K2Is a positive definite design diagonal matrix, omegan1 and ωn2Is the natural frequency of the filter, ζ1 and ζ2In order to design the constants of the two-phase,
Figure FDA00027435813600000311
φ11 and φ12Is the output of two filters, alpha1 and α2Then as an input the information is transmitted,
Figure FDA00027435813600000312
for adaptation of the inertia matrix, δ1＝φ11-α1 and δ2＝φ21-α2Filtering errors, xi, of two filters, respectively1、ξ2 and ξ3Respectively, the state variables of the model-free filter compensation system.
9. The fuzzy adaptive preset performance control method for the unmanned ship dynamic positioning according to claim 1, wherein the method for calculating the output control force/moment of the model-free preset performance controller comprises
Figure FDA0002743581360000041
wherein ,K3 and KcFor positive design matrix, τ is thrust/torque output without considering input saturation limits，s2To account for the velocity error surface vector after the command filter compensates for the error, AtrIs an actuator dynamic matrix.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113220000A (en) * 2021-05-11 2021-08-06 华中科技大学 Unmanned ship path tracking preset performance control method and system for underwater detection operation
CN115268260A (en) * 2022-06-07 2022-11-01 华中科技大学 Unmanned ship preset time trajectory tracking control method and system considering transient performance
CN115617044A (en) * 2022-10-28 2023-01-17 华中科技大学 Non-singular finite time unmanned ship preset performance dynamic positioning control method and system

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103324195A (en) * 2013-06-14 2013-09-25 哈尔滨工程大学 Ship self-adaptive robust course tracking control method based on back stepping method
CN105629721A (en) * 2016-02-01 2016-06-01 金陵科技学院 Second-order nonlinear system no-model control method based on instruction filtering Backstepping
US20160209850A1 (en) * 2014-12-09 2016-07-21 Embry-Riddle Aeronautical University, Inc. System and method for robust nonlinear regulation control of unmanned aerial vehicles syntetic jet actuators
CN108983786A (en) * 2018-08-08 2018-12-11 华南理工大学 A kind of communication context constrains the formation control method of lower mobile robot
CN109507885A (en) * 2018-12-20 2019-03-22 中国海洋大学 Model-free adaption AUV control method based on active disturbance rejection
CN109839934A (en) * 2019-02-26 2019-06-04 华南理工大学 Unmanned water surface ship default capabilities tracking and controlling method based on RISE technology
CN110362075A (en) * 2019-06-26 2019-10-22 华南理工大学 A kind of unmanned boat output feedback formation control design method with default capabilities
RU2721623C1 (en) * 2019-09-30 2020-05-21 Федеральное государственное унитарное предприятие «Государственный научно-исследовательский институт авиационных систем» (ФГУП «ГосНИИАС») Method for determining the instantaneous position of the drift point of an unmanned aerial vehicle from information of an angle measurement channel
CN111290421A (en) * 2020-03-20 2020-06-16 湖南云顶智能科技有限公司 Hypersonic aircraft attitude control method considering input saturation
CN111665721A (en) * 2020-06-17 2020-09-15 国网河南省电力公司经济技术研究院 Flywheel energy storage control system design method for pulse power load regulation

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103324195A (en) * 2013-06-14 2013-09-25 哈尔滨工程大学 Ship self-adaptive robust course tracking control method based on back stepping method
US20160209850A1 (en) * 2014-12-09 2016-07-21 Embry-Riddle Aeronautical University, Inc. System and method for robust nonlinear regulation control of unmanned aerial vehicles syntetic jet actuators
CN105629721A (en) * 2016-02-01 2016-06-01 金陵科技学院 Second-order nonlinear system no-model control method based on instruction filtering Backstepping
CN108983786A (en) * 2018-08-08 2018-12-11 华南理工大学 A kind of communication context constrains the formation control method of lower mobile robot
CN109507885A (en) * 2018-12-20 2019-03-22 中国海洋大学 Model-free adaption AUV control method based on active disturbance rejection
CN109839934A (en) * 2019-02-26 2019-06-04 华南理工大学 Unmanned water surface ship default capabilities tracking and controlling method based on RISE technology
CN110362075A (en) * 2019-06-26 2019-10-22 华南理工大学 A kind of unmanned boat output feedback formation control design method with default capabilities
RU2721623C1 (en) * 2019-09-30 2020-05-21 Федеральное государственное унитарное предприятие «Государственный научно-исследовательский институт авиационных систем» (ФГУП «ГосНИИАС») Method for determining the instantaneous position of the drift point of an unmanned aerial vehicle from information of an angle measurement channel
CN111290421A (en) * 2020-03-20 2020-06-16 湖南云顶智能科技有限公司 Hypersonic aircraft attitude control method considering input saturation
CN111665721A (en) * 2020-06-17 2020-09-15 国网河南省电力公司经济技术研究院 Flywheel energy storage control system design method for pulse power load regulation

Non-Patent Citations (8)

* Cited by examiner, † Cited by third party
Title
CAOYANG YU ET AL.: "Guidance-Error-Based Robust Fuzzy Adaptive Control for Bottom Following of a Flight-Style AUV With Saturated Actuator Dynamics", 《IEEE TRANSACTIONS ON CYBERNETICS》 *
CAOYANG YU ET AL.: "Guidance-Error-Based Robust Fuzzy Adaptive Control for Bottom Following of a Flight-Style AUV With Saturated Actuator Dynamics", 《IEEE TRANSACTIONS ON CYBERNETICS》, vol. 50, no. 5, 31 May 2020 (2020-05-31), pages 1887 - 1899, XP011783450, DOI: 10.1109/TCYB.2018.2890582 *
张杨 等: "受限指令预设性能自适应反演控制器设计", 《控制与决策》 *
张杨 等: "受限指令预设性能自适应反演控制器设计", 《控制与决策》, vol. 32, no. 7, 31 July 2017 (2017-07-31), pages 1253 - 1258 *
胡云安 等: "严格反馈非线性***预设性能backstepping控制器设计", 《控制与决策》 *
胡云安 等: "严格反馈非线性***预设性能backstepping控制器设计", 《控制与决策》, vol. 29, no. 8, 31 August 2014 (2014-08-31), pages 1509 - 1512 *
胡云安 等: "初始误差未知的不确定***预设性能反演控制", 《华中科技大学学报（自然科学版）》 *
胡云安 等: "初始误差未知的不确定***预设性能反演控制", 《华中科技大学学报（自然科学版）》, vol. 42, no. 8, 31 August 2014 (2014-08-31), pages 43 - 47 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113220000A (en) * 2021-05-11 2021-08-06 华中科技大学 Unmanned ship path tracking preset performance control method and system for underwater detection operation
CN113220000B (en) * 2021-05-11 2022-12-02 华中科技大学 Unmanned ship path tracking preset performance control method and system for underwater detection operation
CN115268260A (en) * 2022-06-07 2022-11-01 华中科技大学 Unmanned ship preset time trajectory tracking control method and system considering transient performance
CN115268260B (en) * 2022-06-07 2023-07-25 华中科技大学 Unmanned ship preset time track tracking control method and system considering transient performance
CN115617044A (en) * 2022-10-28 2023-01-17 华中科技大学 Non-singular finite time unmanned ship preset performance dynamic positioning control method and system

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