基于神经状态和扰动观测器的独轮车机器人滑模控制

Barhoumi Nawress, Asma Najet Gharbi Lakhal, Naceur Benhadj Braïek
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引用次数: 0

摘要

提出了一种基于神经状态观测器(NSO)和非线性干扰观测器(NDO)的改进滑模控制方法(SMC)的独轮车移动机器人混合控制方法。利用Lyapunov的直接方法一方面保证了闭环控制的稳定性,另一方面保证了基于反向传播算法的神经状态观测器的稳定性。仿真结果显示了所提出的混合控制器在移动机器人速度和轨迹跟踪方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural State and Disturbance Observer-based Sliding Mode Control of a Unicycle Robot
This paper presents the synthesis of a hybrid control applied to a Unicycle Mobile Robot (UMR) based on modified Sliding Mode Control approach (SMC) integrated with Neural State Observer (NSO) and Nonlinear Disturbance Observer (NDO). Furthermore, Lyapunov's direct method is used to ensure the stability of the closed-loop control on the one hand, and the stability of the neural state observer based on the backpropagation algorithm on the other hand. The advantages of the presented hybrid controller for velocity and tracking the trajectory of a mobile robot are revealed by simulation results.
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