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首页> 外文会议>IEEE Industry Applications Society Annual Meeting >Nonlinear Robust Optimal Control via Adaptive Dynamic Programming of Permanent-Magnet Linear Synchronous Motor Drive for Uncertain Two-Axis Motion Control System
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Nonlinear Robust Optimal Control via Adaptive Dynamic Programming of Permanent-Magnet Linear Synchronous Motor Drive for Uncertain Two-Axis Motion Control System

机译：不确定线性两轴运动控制系统永磁直线同步电动机驱动器自适应动态编程的非线性鲁棒最优控制

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摘要

In this paper, a nonlinear robust optimal control (NROC) for uncertain two-axis motion control system via adaptive dynamic programming (ADP) and neural networks (NNs) is proposed to improve the robustness against parameter variations and compounded disturbances. The two-axis motion control system is an X-Y table driven by two permanent-magnet linear synchronous motors (PMLSMs) servo drives. The tracking control problem of the nonlinear X-Y table with uncertainties is transformed to a regulation problem. Then, it is solved by an infinite horizon optimal control scheme using a critic NN. Consequently, the NN is developed via ADP learning algorithm to facilitate the online solution of the modified Hamilton-Jacobi-Bellman (HJB) equation corresponding to the nominal system for approximating the optimal control law. The uniform ultimate boundedness of the closed-loop system is proved using the Lyapunov approach and the tracking error asymptotically converges to a residual set. The validity and robustness of the proposed control system are verified by experimental analysis. The control algorithms have been developed in a control computer based on a dSPACE DS1104 DSP control computer. From the experimental results, the dynamic behaviors of the two-axis motion control system using the proposed NROC can achieve robust optimal tracking control performance against parameter uncertainties and compounded disturbances.
机译：本文提出了一种通过自适应动态规划（ADP）和神经网络（NNs）的不确定两轴运动控制系统的非线性鲁棒最优控制（NROC），以提高其对参数变化和复合干扰的鲁棒性。两轴运动控制系统是一个X-Y工作台，由两个永磁线性同步电动机（PMLSM）伺服驱动器驱动。将具有不确定性的非线性X-Y表的跟踪控制问题转化为调节问题。然后，通过使用评论者NN的无限层最优控制方案来解决该问题。因此，通过ADP学习算法开发了NN，以方便在线求解对应于标称系统的经修改的Hamilton-Jacobi-Bellman（HJB）方程，以逼近最佳控制律。使用Lyapunov方法证明了闭环系统的一致最终有界性，并且跟踪误差渐近收敛到残差集。通过实验分析验证了所提出控制系统的有效性和鲁棒性。控制算法是在基于dSPACE DS1104 DSP控制计算机的控制计算机中开发的。从实验结果来看，使用所提出的NROC的两轴运动控制系统的动态行为可以针对参数不确定性和复合干扰获得鲁棒的最优跟踪控制性能。

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