控制理论(社会学)
运动学
模糊逻辑
自适应控制
模糊控制系统
滑模控制
稳健性(进化)
趋同(经济学)
指数稳定性
终端滑动模式
计算机科学
控制器(灌溉)
鲁棒控制
机器人
控制工程
控制系统
工程类
人工智能
非线性系统
控制(管理)
经济增长
化学
生物
生物化学
经典力学
量子力学
农学
物理
电气工程
经济
基因
作者
Mohammad Reza Soltanpour,Saeed Zaare
摘要
Summary Basic features such as convergence time and speed, number‐action control coefficients, free chattering, and proof of stability are significant in the design process and sliding mode control (SMC) efficiency. In this article, we propose an adaptive fuzzy global fast terminal SMC (AFGFTSMC) to handle the mentioned features in the task space control of the robot manipulator in the presence of dynamic and kinematic uncertainties. First, perturbed joint space dynamic equations of the system are transferred to task space, and a broad range of uncertainties are considered there. Then, a global fast terminal SMC (GFTSMC) is proposed for robot manipulators in task space, in which a flexible sliding surface improves the convergence time. Next, to have an intelligent adjustment of the sliding surface coefficients, which leads to a much faster convergence rate, a fuzzy approximator with just seven fuzzy rules is presented. In the following, to access the boundaries of the existing uncertainties, an adaptive fuzzy approximator is proposed, which has five fuzzy rules and only one adaptive law, increases the system's robustness, and eliminates the effect of chattering. Mathematical proof shows that the task space closed‐loop control system under the proposed AFGFTSMC and in the presence of dynamic and kinematic uncertainties has a finite‐time global asymptotic stability. The theoretical evidence and simulation results, which are conducted on a 2‐link robot manipulator, confirm the good efficiency of the proposed controller.
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