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Reinforcement Learning Behavioral Control for nonlinear autonomous system

IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1561-1573页

作者： Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang the College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian ProvinceFuzhou 350108 G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear *** this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error ***,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission *** with existing mission supervisors,the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural *** the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control *** with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and *** error signals are proved to be semi-globally uniformly ultimately bounded(SGUUB).Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers,respectively.

关键词： Behavioral control mission supervisor nonlinear autonomous system reinforcement learning

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Generalized hyperbolic perturbation method for homoclinic solutions of strongly nonlinear autonomous systems

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Applied Mathematics and Mechanics(English Edition) 2012年第9期33卷 1137-1152页

作者：陈洋洋燕乐纬佘锦炎陈树辉 Key Laboratory of Vibration Control and Structural Safety of Ministry of Education of China Guangzhou University Department of Engineering Mechanics Guangzhou University Department of Mechanical Engineering The University of Hong KongPokfulam Department of Applied Mechanics and Engineering Sun Yat-sen University

A generalized hyperbolic perturbation method is presented for homoclinic solutions of strongly nonlinear autonomous oscillators, in which the perturbation proce- dure is improved for those systems whose exact homoclinic generating solutions cannot be explicitly derived. The generalized hyperbolic functions are employed as the basis functions in the present procedure to extend the validity of the hyperbolic perturbation method. Several strongly nonlinear oscillators with quadratic, cubic, and quartic nonlinearity are studied in detail to illustrate the efficiency and accuracy of the present method.

关键词： generalized hyperbolic perturbation method nonlinear autonomous system homoclinic solution

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