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indirect adaptive fuzzy-regulated optimal control for unknown continuous-time nonlinear systems

Frontiers of Information Technology & Electronic Engineering 2021年第2期22卷 155-169页

作者： Haiyun ZHANG Deyuan MENG Jin WANG Guodong LU State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Department of Mechatronic Engineering China University of Mining and TechnologyXuzhou 221116China

We present a novel indirect adaptive fuzzy-regulated optimal control scheme for continuous-time nonlinear systems with unknown dynamics,mismatches,and ***,the Hamilton-Jacobi-Bellman(HJB)equation associated with its performance function is derived for the original nonlinear *** existing adaptive dynamic programming(ADP)approaches,this scheme uses a special non-quadratic variable performance function as the reinforcement medium in the actor-critic *** adaptive fuzzy-regulated critic structure is correspondingly constructed to configure the weighting matrix of the performance function for the purpose of approximating and balancing the HJB equation.A concurrent self-organizing learning technique is designed to adaptively update the critic *** on this particular critic,an adaptive optimal feedback controller is developed as the actor with a new form of augmented Riccati equation to optimize the fuzzy-regulated variable performance function in real *** result is an online indirect adaptive optimal control mechanism implemented as an actor-critic structure,which involves continuous-time adaptation of both the optimal cost and the optimal control *** convergence and closed-loop stability of the proposed system are proved and *** examples and comparisons show the effectiveness and advantages of the proposed method.

关键词： indirect adaptive optimal control Hamilton-Jacobi-Bellman equation Fuzzy-regulated critic adaptive optimal control actor Actor-critic structure Unknown nonlinear systems

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