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Critic Only Policy Iteration-based Zero-sum Neuro-optimal Control of Modular and Reconfigurable Robots with uncertain disturbance via Adaptive Dynamic Programming

机译:通过自适应动态规划的具有不确定干扰的模块化和可重构机器人基于关键决策策略迭代的零和神经最优控制

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A critic only policy iteration (COPI) scheme-based zero-sum neuro-optimal control method has been presented via adaptive dynamic programming (ADP) to address optimal trajectory velocity and tracking control of modular and reconfigurable robots (MRRs) problem. Based on policy iteration (PI) and ADP method, Hamilton-Jacobi-Issacs (HJI) equation is addressed by using only critic neural network (NN). The approximated optimal control can be obtained. Closed-loop system is proved to be asymptotic stable according to the Lyapunov theory. At last, simulations are demonstrated to show effectiveness of method.
机译:通过自适应动态编程(ADP),提出了一种仅基于评论者策略迭代(COPI)方案的零和神经最优控制方法,以解决模块化和可重构机器人(MRR)问题的最优轨迹速度和跟踪控制问题。基于策略迭代(PI)和ADP方法,仅使用评论者神经网络(NN)解决了Hamilton-Jacobi-Issacs(HJI)方程。可以获得近似的最佳控制。根据李雅普诺夫理论,证明闭环系统是渐近稳定的。最后,通过仿真证明了该方法的有效性。

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