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Adaptive Actor–Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances

机译:具有输入扰动的部分未知非线性系统的基于自适应Actor-Critic设计的整体滑模控制

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This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor–critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.
机译:本文关注的是一类具有输入扰动和未知非线性项的非线性系统的整体滑模控制问题,它是通过自适应行为者(AC)控制方法实现的。主要目的是设计基于自适应动态规划(ADP)方法的滑模控制方法,以使具有时变扰动的闭环系统稳定,并能获得几乎最佳的滑模动力学性能。保证。第一步,设计基于神经网络(NN)的观测器和扰动观测器,分别对未知的非线性项进行近似并估计输入扰动。基于NN近似值和扰动估计,构造了滑模控制的不连续部分,以消除扰动的影响并获得预期的等效滑模动力学。然后,提出了一种具有AC结构的ADP方法,以在线学习滑模动力学的最优控制。开发了重构的调整律,以确保滑模动力学的稳定性以及评论者和演员NN权重的收敛。最后,仿真结果表明了该方法的有效性。

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