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Sliding mode control for an aerodynamic missile based on backstepping design

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控制理论与应用（英文版） 2005年第1期3卷 71-75页

作者： WenjinGU HongchaoZHAO ChangpengPAN Faculty301 NavalAeronauticalEngineeringInstituteYantaiShandong264001China

In order to solve the mismatched uncertainties of a class of nonlinearsystems, a control method of sliding mode control (SMC) based on the backstepping design isproposed. It introduces SMC in to the last step of backstepping design to modify the backsteppingalgorithm. This combination not only enables the generalization of the backstepping design to beapplied to more general nonlinear systems, but also makes the SMC method become effective in solvingthe mismatched uncertainties. The SMC based on the backstepping design is applied to the flightcontrol system design of an aerodynamic missile. The control system is researched throughsimulation. The simulation results show the effectiveness of the proposed control method.

关键词： mismatched uncertainties sliding mode control backstepping design aerodynamic missile

Observer-Based Adaptive Fuzzy Tracking Control Using Integral Barrier Lyapunov Functionals for A Nonlinear System With Full State Constraints

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IEEE/CAA Journal of Automatica Sinica 2021年第3期8卷 617-627页

作者： Wei Zhao Yanjun Liu Lei Liu School of Electrical Engineering Liaoning University of TechnologyJinzhou 121001China College of Science Liaoning University of TechnologyJinzhou 121001China

A new fuzzy adaptive control method is proposed for a class of strict feedback nonlinear systems with immeasurable states and full *** fuzzy logic system is used to design the approximator,which deals with uncertain and continuous functions in the process of backstepping *** use of an integral barrier Lyapunov function not only ensures that all states are within the bounds of the constraint,but also mixes the states and errors to directly constrain the state,reducing the conservativeness of the constraint satisfaction *** that the states in most nonlinear systems are immeasurable,a fuzzy adaptive states observer is constructed to estimate the unknown *** with adaptive backstepping technique,an adaptive fuzzy output feedback control method is *** proposed control method ensures that all signals in the closed-loop system are bounded,and that the tracking error converges to a bounded tight set without violating the full state *** simulation results prove the effectiveness of the proposed control scheme.

关键词： Adaptive control backstepping design integral barrier Lyapunov function(iBLF) states observer

Adaptive Fuzzy backstepping Tracking Control for Flexible Robotic Manipulator

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IEEE/CAA Journal of Automatica Sinica 2021年第12期8卷 1923-1930页

作者： Wanmin Chang Yongming Li Shaocheng Tong Department of College of Electrical Engineering Liaoning University of TechnologyJinzhou121001China Department of College of Science Liaoning University of TechnologyJinzhou121001China

In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator *** considered system contains unknown nonlinearfunction and actuator *** logic systems(FLSs)and a smooth function are used to approximate the unknownnonlinearities and the actuator saturation,*** com-bining the command-filter technique with the backsteppingdesign algorithm,a novel adaptive fuuzy tracking backsteppingcontrol method is *** is proved that the adaptive fuuzycontrol scheme can guarantee that all the variables in the closed-loop system are bounded,and the system output can track thegiven reference signal as close as *** results areprovided to illustrate the effectiveness of the proposed approach.

关键词： Actuator saturation backstepping design command-filter technique flexible robotic manipulator fuzzy adaptive control

Output-Feedback Based Simplified Optimized backstepping Control for Strict-Feedback Systems with Input and State Constraints

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1119-1132页

作者： Jiaxin Zhang Kewen Li Yongming Li College of Science Liaoning University of TechnologyJinzhou 121001China Institute of Automation Qufu Normal UniversityQufu 273165China

In this paper,an adaptive neural-network(NN)output feedback optimal control problem is studied for a class of strict-feedback nonlinear systems with unknown internal dynamics,input saturation and state *** networks are used to approximate unknown internal dynamics and an adaptive NN state observer is developed to estimate immeasurable *** the framework of the backstepping design,by employing the actor-critic architecture and constructing the tan-type Barrier Lyapunov function(BLF),the virtual and actual optimal controllers are *** order to accomplish optimal control effectively,a simplified reinforcement learning(RL)algorithm is designed by deriving the updating laws from the negative gradient of a simple positive function,instead of employing existing optimal control *** addition,to ensure that all the signals in the closed-loop system are bounded and the output can follow the reference signal within a bounded error,all state variables are confined within their compact sets all ***,a simulation example is given to illustrate the effectiveness of the proposed control strategy.

关键词： backstepping design immeasurable states neuralnetworks(NNs) optimal control state constraints

Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone

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Science China(Information Sciences) 2014年第3期57卷 276-287页

作者： LIU YanJun LIU Lei TONG ShaoCheng College of Science Liaoning University of Technology

In this paper,the stability and control issues of a class of uncertain nonlinear discrete-time systems in the strict feedback form are *** dead-zone input in the systems,whose property is non-symmetric and discretized,is *** unknown functions in the systems are approximated by using the radial basis function neural networks(RBFNNs).backstepping design procedure is employed in the controller and the adaptation laws *** analysis method is utilized to prove the stability of the closed-loop system.A simulation example is given to illustrate the efectiveness of the proposed approach.

关键词： adaptive control RBF neural network non-symmetric dead-zone backstepping design uncertain nonlinear systems

Adaptive Fuzzy Dynamic Surface Control for Uncertain Nonlinear Systems

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International Journal of Automation and computing 2009年第4期6卷 385-390页

作者： Xiao-Yuan Luo Zhi-Hao Zhu Xin-Ping Guan Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 PRC

In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.

关键词： Uncertain nonlinear systems fuzzy logic system dynamic surface control backstepping design

Experimental Validation of Nussbaum Gain Adaptive Control for a Polymer Composite Based Electromagnetic Micromirror 36

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Experimental Validation of Nussbaum Gain Adaptive Control fo...

Direct Adaptive Fuzzy Based backstepping Control of Semi Strict Feedback Nonlinear Systems

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作者： Jiazheng Tan Weijie Sun John T.W.Yeow Department of Automation Science and Engineering South China University of Technology Advanced Micro/Nano Devices Laboratory Systems Design EngineeringUniversity of Waterloo

ISBN: (纸本)9781538629185

In this article, an adaptive controller based on Nussbaum gain technique and backstepping method is designed for a polymer composite based hard-magnetic micromirror. With the Nussbaum gain exploited, the unknown control direction problem is solved. As a result, the closed-loop system with proposed controller design is able to track the desired reference signal asymptotically. The effectiveness of the adaptive controller is verified by experimental results on a micromirror-based platform.

关键词： Nussbaum gain backstepping design Unknown control direction Electromagnetic micromirror

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Computer Technology and Application 2011年第11期2卷 884-892页

作者： Raoudha Ben Khaled Chaouki Mnasri Moncef Gasmi Department of Electrical Engineering ISI Ariana Tunisia Department of Electronics Engineering ISSAT Mateur Tunisia Department of Physics and Instrumentation INSA T Tunis Tunisia Unit~ de Recherche en Automatique et Informatique Industrielle （URAII） INSAT Universite de Carthage Tunsia

In this paper, a direct adaptive fuzzy tracking control is proposed for a class of uncertain single-input single-output nonlinear semi-strict feedback systems. Based on Takagi-Sugeno type fuzzy systems, a direct adaptive fuzzy tracking controller is developed by using the backstepping approach. The main advantage of the developed method is that for an n-th order system, only one parameter is needed to be adjusted online. It is proven that, under the appropriate assumptions, the developed scheme can achieve that the output system converges to a small neighborhood of the reference signal and all the signals in the closed-loop system remain bounded. The efficacy of the proposed algorithm is investigated by an illustrative simulation example of one link robot.

关键词： Direct adaptive fuzzy control perturbed nonlinear systems strict feedback form backstepping design output tracking

Adaptive L_2 control of nonlinear systems using neural networks

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控制理论与应用（英文版） 2004年第4期2卷 332-338页

作者： HuaijingQU YingZHANG FengrongSUN SchoolofInformationScienceandEngineering ShandongUniversityJinanShandong250100China SingaporeInstituteofManufacturingTechnology NanyangDrive71638075Singapore

An adaptive neural network controller is developed to achieve output-tracking of a class of nonlinear systems. The global L 2 stability of the closed-loop system is established. The proposed control design overcomes the limitation of the conventional adaptive neural control design where the modeling error brought by neural networks is assumed to be bounded over a compact set. Moreover, the generalized matching conditions are also relaxed in the proposed L 2 control design as the gains for the external disturbances entering the system are allowed to have unknown upper bounds.

关键词： Adaptive control Neural network Nonlinear systems Stability L 2 controller backstepping design