scholarly journals Backstepping Control Based on Constrained Command Filter for Hypersonic Flight Vehicles with AOA and Actuator Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Junbao Wei ◽  
Haiyan Li ◽  
Ming Guo ◽  
Jing Li ◽  
Huang Huang
Keyword(s):  
Tracking Error ◽  
Lyapunov Stability Theory ◽  
Backstepping Control ◽  
Control Input ◽  
Tracking Errors ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Control Scheme ◽  
Actuator Constraints ◽  
Command Filter

An antisaturation backstepping control scheme based on constrained command filter for hypersonic flight vehicle (HFV) is proposed with the consideration of angle of attack (AOA) constraint and actuator constraints of amplitude and rate. Firstly, the HFV system model is divided into velocity subsystem and height subsystem. Secondly, to handle AOA constraint, a constrained command filter is constructed to limit the amplitude of the AOA command and retain its differentiability. And the constraint range is set in advance via a prescribed performance method to guarantee that the tracking error of the AOA meets the constraint conditions and transient and steady performance. Thirdly, the proposed constrained command filter is combined with the auxiliary system for actuator constraints, which ensures that the control input meets the limited requirements of amplitude and rate, and the system is stable. In addition, the tracking errors of the system are proved to be ultimately uniformly bounded based on the Lyapunov stability theory. Finally, the effectiveness of the proposed method is verified by simulation.

A novel adaptive dynamic surface control scheme of hypersonic flight vehicles with thrust and actuator constraints

2017 ◽  
Vol 40 (4) ◽  
pp. 1362-1374 ◽  
Author(s):  
Shen Zhang ◽  
Qing Wang ◽  
Chaoyang Dong
Keyword(s):  
Control Method ◽  
Dynamic Surface Control ◽  
Tracking Errors ◽  
Dynamic Surface ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Surface Control ◽  
Adaptive Law ◽  
Control Scheme ◽  
Actuator Constraints

In this paper, the nonlinear adaptive velocity and altitude tracking controller is developed for the longitudinal dynamics of generic air-breathing hypersonic flight vehicles. The proposed control scheme is designed using dynamic surface control method. The velocity and altitude subsystems are transformed into the linearly parameterized form for the convenience of adaptive law design. Both of the thrust and actuator constraints are explicitly considered. For thrust constraint, two cases are analyzed when the fuel-to-air ratio reaches its max and min values. A novel adaptive law is proposed to avoid over or less estimation in thrust saturation occasion. For actuator constraint, a magnitude and rate limiting filter is incorporated. The filter guarantees that the control signal is applicable for the actuator. It is shown that with the application of the proposed control scheme, all signals of the closed-loop system are uniformly ultimately bounded and the velocity and altitude tracking errors converge to a residual set which is arbitrarily small. Simulation results are demonstrated to show the effectiveness and superiority of the proposed control scheme.

scholarly journals Novel Prescribed Performance Control Scheme for Flexible Hypersonic Flight Vehicles with Nonaffine Dynamics and Neural Approximation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yong Liu ◽  
Gang Li ◽  
Yuchen Li ◽  
Yahui Wu
Keyword(s):  
Feedback Form ◽  
Tracking Errors ◽  
Prescribed Performance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Complex Design ◽  
Control Scheme ◽  
Integral Controller ◽  
Proportional Integral Controller ◽  
And Control

This study develops a novel neural-approximation-based prescribed performance controller for flexible hypersonic flight vehicles (HFVs). Firstly, a new prescribed performance mechanism is exploited, which develops new performance functions guaranteeing velocity and altitude tracking errors with small overshoots. Compared with the existing prescribed performance mechanism, it has better preselected transient and steady-state performance. Then, the nonaffine model of HFV is decomposed into a velocity subsystem and an altitude subsystem. A prescribed performance-based proportional-integral controller is designed in the velocity subsystem. In the altitude subsystem, the model is expressed as a nonaffine pure feedback form, and control inputs are derived from neural approximations. In order to reduce the amount of computation, only one neural network approximator is used to approximate the subsystem uncertainties, and an advanced regulation algorithm is applied to the devise adaptive law for neural estimation. At the same time, the complex design process of back-stepping can be avoided. Finally, numerical simulation results are presented to verify the efficiency of the design.

scholarly journals Neural Network-Based Adaptive Backstepping Control for Hypersonic Flight Vehicles with Prescribed Tracking Performance

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhu Guoqiang ◽  
Liu Jinkun
Keyword(s):  
Neural Control ◽  
Closed Loop ◽  
Tracking Error ◽  
Closed Loop System ◽  
Adaptive Backstepping ◽  
Adaptive Neural Control ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Control Scheme ◽  
Constraint Variable

An adaptive neural control scheme is proposed for a class of generic hypersonic flight vehicles. The main advantages of the proposed scheme include the following: (1) a new constraint variable is defined to generate the virtual control that forces the tracking error to fall within prescribed boundaries; (2) RBF NNs are employed to compensate for complex and uncertain terms to solve the problem of controller complexity; (3) only one parameter needs to be updated online at each design step, which significantly reduces the computational burden. It is proved that all signals of the closed-loop system are uniformly ultimately bounded. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

scholarly journals Data-driven automatic parking constrained control for four-wheeled mobile vehicles

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141666366 ◽  
Author(s):  
Wenxu Yan ◽  
Jing Deng ◽  
Dezhi Xu
Keyword(s):  
Orientation Angle ◽  
Design Procedure ◽  
Data Driven ◽  
Control Input ◽  
Constrained Control ◽  
Tracking Errors ◽  
Rapid Responses ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Automatic Parking

In this article, a novel data-driven constrained control scheme is proposed for automatic parking systems. The design of the proposed scheme only depends on the steering angle and the orientation angle of the car, and it does not involve any model information of the car. Therefore, the proposed scheme-based automatic parking system is applicable to different kinds of cars. In order to further reduce the desired trajectory coordinate tracking errors, a coordinates compensation algorithm is also proposed. In the design procedure of the controller, a novel dynamic anti-windup compensator is used to deal with the change magnitude and rate saturations of automatic parking control input. It is theoretically proven that all the signals in the closed-loop system are uniformly ultimately bounded based on Lyapunov stability analysis method. Finally, a simulation comparison among the proposed scheme with coordinates compensation and Proportion Integration Differentiation (PID) control algorithm is given. It is shown that the proposed scheme with coordinates compensation has smaller tracking errors and more rapid responses than PID scheme.

scholarly journals Adaptive Predefined Performance Neural Control for Robotic Manipulators with Unknown Dead Zone

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Shifen Shao ◽  
Kaisheng Zhang ◽  
Jun Li ◽  
Jirong Wang
Keyword(s):  
Neural Control ◽  
Dead Zone ◽  
Tracking Error ◽  
Transient Behavior ◽  
Robotic Manipulators ◽  
System Stability ◽  
Control Effect ◽  
Tracking Errors ◽  
Control Scheme ◽  
Funnel Control

This paper proposes an adaptive predefined performance neural control scheme for robotic manipulators in the presence of nonlinear dead zone. A neural network (NN) is utilized to estimate the model uncertainties and unknown dynamics. An improved funnel function is designed to guarantee the transient behavior of the tracking error. The proposed funnel function can release the assumption on the conventional funnel control. Then, an adaptive predefined performance neural controller is proposed for robotic manipulators, while the tracking errors fall within a prescribed funnel boundary. The closed-loop system stability is proved via Lyapunov function. Finally, the numerical simulation results based on a 2-DOF robotic manipulator illustrate the control effect of the presented approach.

scholarly journals Prescribed Performance Tracking Control for Hypersonic Flight Vehicles with Model Uncertainties

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Siyuan Zhao ◽  
Xiaobing Li ◽  
Xiangwei Bu ◽  
Dongyang Zhang
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Longitudinal Motion ◽  
Model Uncertainties ◽  
Prescribed Performance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Performance Tracking ◽  
Control Objective ◽  
Proportional Integral Controller

This paper proposes a novel prescribed performance tracking control for a hypersonic flight vehicle (HFV) with model uncertainties. Firstly, a HFV longitudinal motion model is decomposed into a velocity subsystem and an altitude subsystem. Meanwhile, considering the uncertainties of the model, the velocity subsystem and altitude subsystem are directly expressed as the forms with unknown nonaffine functions. Secondly, a novel performance function without initial error is proposed for limiting the tracking error into a prescribed range. Then, for the altitude subsystem, the control objective is changed by model transformation and the prescribed performance backstepping controller is designed. For the velocity subsystem, a prescribed performance proportional-integral controller is proposed which has better engineering practicability. The designed controller is not only simple in form but also has few calculating parameters. Finally, the simulation results show that the proposed controller has good practicability.

Strictly-lower-convex-function-constructing disturbance observer based adaptive back stepping control for hypersonic flight vehicles

2017 ◽  
Vol 232 (13) ◽  
pp. 2552-2564
Author(s):  
Jingxing Zuo ◽  
Yunjie Wu ◽  
Lianghua Sun
Keyword(s):  
Convex Function ◽  
Flight Control ◽  
Disturbance Observer ◽  
Sliding Mode ◽  
Tracking Error ◽  
Small Region ◽  
Control Laws ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Adaptive Laws

This study concerns with the attitude and velocity tracking control problem for the longitudinal model of hypersonic flight vehicles, which is nonlinear in aerodynamics with model uncertainties and external disturbances. By employing back stepping sliding mode method and the strictly-lower-convex-function-constructing nonlinear disturbance observer (SNDOB), a novel composite controller is proposed to guarantee the system tracking error to converge to a small region containing the origin. Besides, several proper adaptive laws are also introduced to make the controller avoid of the differential explosion problem and be chatter-free. Compared with other robust flight control approaches, key novelties of the developed method are that one new SNDOB is proposed and drawn into the virtual control laws at each step to compensate the disturbances and that adaptive laws are utilized to simplify the tedious and complicated differential operations. Finally, it is demonstrated by the simulation results that the new method exhibits not only an excellent robustness but also a better disturbance rejection performance than the convention approach.

Design of Missile Longitudinal Control System Based on Backstepping Control

2014 ◽  
Vol 496-500 ◽  
pp. 1401-1406
Author(s):  
Mei Hong Li ◽  
Jian Yin ◽  
Xue Yang Sun ◽  
Jin Xiang Xu ◽  
Mei Mei Zhang
Keyword(s):  
Control System ◽  
Control Method ◽  
Input Saturation ◽  
Lyapunov Stability Theory ◽  
Feedback System ◽  
Backstepping Control ◽  
Control Input ◽  
Backstepping Method ◽  
Longitudinal Control ◽  
And Control

Missile control system is not block strict feedback system which is suitable to use backstepping method. So in this paper, a backstepping control method is proposed to design a missile longitudinal autopilot and is proved to be asymptotically stable by Lyapunov stability theory. The simulation results show that the designed system can still track commands quickly and accurately and is robust with aerodynamic perturbation and control input saturation.

scholarly journals Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

2017 ◽  
Vol 14 (1) ◽  
pp. 172988141668270 ◽  
Author(s):  
Zhonghua Wu ◽  
Jingchao Lu ◽  
Jingping Shi ◽  
Qing Zhou ◽  
Xiaobo Qu
Keyword(s):  
Neural Control ◽  
Tracking Error ◽  
Flight Vehicle ◽  
Model Uncertainties ◽  
Adaptive Neural Control ◽  
Prescribed Performance ◽  
Hypersonic Flight Vehicle ◽  
Hypersonic Flight ◽  
Control Scheme ◽  
Robust Adaptive

A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

scholarly journals Neural Networks Approximator Based Robust Adaptive Controller Design of Hypersonic Flight Vehicles Systems Coupled with Stochastic Disturbance and Dynamic Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Guoqiang Zhu ◽  
Lingfang Sun ◽  
Xiuyu Zhang
Keyword(s):  
Controller Design ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Stochastic Disturbance ◽  
Hypersonic Flight ◽  
Flight Vehicles ◽  
Uncertain Dynamics ◽  
Robust Adaptive ◽  
And Performance ◽  
Dynamic Uncertainties

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm.

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