基于遗传算法的模糊滑模控制非完整移动机器人的镇定

Wei-Ming Lee, Han-Pang Huang
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引用次数: 6

摘要

本文将模糊逻辑控制原理与滑模控制理论相结合,实现移动机器人在非完整运动约束下的稳定。为了提高FLC的跟踪性能,采用遗传算法搜索FLC的标度因子。仿真结果表明,SMC(滑模控制)、FSMC(模糊控制)和GA-FSMC(基于ga的FSMC)三种控制方法均能使移动机器人在/spl phi/=0时稳定在原点。然而,GA-FSMC提供了一种系统的搜索比例因子的方法,从而提高了系统响应的瞬态性能,减少了导航路径的长度。
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Stabilization of nonholonomic mobile robots by a GA-based fuzzy sliding mode control
In this study, fuzzy logic control principle and sliding mode control theory are combined to stabilize a mobile robot under nonholonomic kinematic constraints. In order to improve the tracking performance, the scaling factors of FLC are searched by genetic algorithms (GAs). The simulation results show that all three control approaches, SMC (sliding mode control), FSMC (fuzzy-SMC) and GA-FSMC (GA-based FSMC) can stabilize the mobile robot to the origin with /spl phi/=0. However the GA-FSMC provides a systematic way to search the scaling factors, and thus improves the transient performance of the system response and reduces the path length for navigation.
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