Unified Adaptive Neural Network H∞ Control of Uncertain Wheeled Mobile Robots

Abstract

Abstract: A smooth global unified controller of trajectory tracking and stabilization was proposed for nonholomomic wheeled mobile robots based on adaptive neural network control and H∞ control. Firstly, the system control inputs were expanded by transverse function method, a nonsingular full drive system which was equivalent to original system was established with decoupled input-output. Then an adaptive neural network H∞ controller was designed for the new system, such that the complex system uncertainty was compensated effectively by the adaptive neural network. Disturbances and approximation errors were attenuated with a prescribed disturbance lever by the H∞ control. Adaptability of the controller were further improved, and the control performance was optimized. The effectiveness of the algorithm were verified by simulation results.

Key words: wheeled mobile robot, unified control of trajectory tracking and stabilization, adaptive neural network, H&infin, control, transverse function

摘要： 提出了一种基于自适应神经网络控制和H∞控制的轮式移动机器人光滑全局跟踪和镇定统一的控制器。首先采用横截函数方法，扩展系统控制输入，建立与原系统等价的、输入输出完全解耦的无奇异全驱动系统，再对新系统设计自适应神经网络H∞控制器。自适应神经网络控制可有效补偿系统的复杂不确定项。H∞控制器可同时对系统扰动和神经网络逼近误差进行预定水平抑制，进一步提高控制器的适应性，优化系统的控制性能。仿真结果验证了算法的有效性。

关键词: 轮式移动机器人；轨迹跟踪与镇定统一控制；自适应神经网络；H&infin, 控制；横截函数

CLC Number:

TP24

YE Jinhua, WU Haibin. Unified Adaptive Neural Network H∞ Control of Uncertain Wheeled Mobile Robots[J]. China Mechanical Engineering.

叶锦华, 吴海彬. 不确定轮式移动机器人统一自适应神经网络H∞控制[J]. 中国机械工程.

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