典型文献
Trajectory Tracking Control for Under-Actuated Hovercraft Using Differential Flatness and Reinforcement Learning-Based Active Disturbance Rejection Control
文献摘要：
This paper proposes a scheme of trajectory tracking control for the hovercraft.Since the model of the hovercraft is under-actuated,nonlinear,and strongly coupled,it is a great challenge for the controller design.To solve this problem,the control scheme is divided into two parts.Firstly,we employ differential flatness method to find a set of flat outputs and consider part of the nonlinear terms as uncertainties.Consequently,we convert the under-actuated system into a full-actuated one.Secondly,a reinforcement learning-based active disturbance rejection controller(RL-ADRC)is designed.In this method,an extended state observer(ESO)is designed to estimate the uncertainties of the system,and an actorcritic-based reinforcement learning(RL)algorithm is used to approximate the optimal control strategy.Based on the output of the ESO,the RL-ADRC compensates for the total uncertainties in real-time,and simultaneously,generates the optimal control strategy by RL algorithm.Simulation results show that,compared with the traditional ADRC method,RL-ADRC does not need to manually tune the controller parameters,and the control strategy is more robust.
文献关键词：
中图分类号：
作者姓名：
KONG Xiangyu;XIA Yuanqing;HU Rui;LIN Min;SUN Zhongqi;DAI Li
作者机构：
School of Automation,Beijing Institute of Technology,Beijing 100190,China
文献出处：
引用格式：
[1]KONG Xiangyu;XIA Yuanqing;HU Rui;LIN Min;SUN Zhongqi;DAI Li-.Trajectory Tracking Control for Under-Actuated Hovercraft Using Differential Flatness and Reinforcement Learning-Based Active Disturbance Rejection Control)[J].系统科学与复杂性学报（英文版）,2022(02):502-521
A类：
Hovercraft,Flatness,hovercraft,actorcritic
B类：
Trajectory,Tracking,Control,Under,Actuated,Using,Differential,Reinforcement,Learning,Based,Active,Disturbance,Rejection,This,paper,proposes,scheme,trajectory,tracking,Since,model,under,actuated,nonlinear,strongly,coupled,great,challenge,controller,To,solve,this,problem,divided,into,two,parts,Firstly,we,employ,differential,flatness,method,find,set,outputs,consider,terms,uncertainties,Consequently,convert,system,full,one,Secondly,reinforcement,learning,active,disturbance,rejection,RL,ADRC,designed,In,extended,state,observer,ESO,estimate,algorithm,used,approximate,optimal,strategy,compensates,total,real,simultaneously,generates,by,Simulation,results,show,that,compared,traditional,does,not,need,manually,tune,parameters,more,robust
AB值：
0.545682
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