【作者】 冯永锋； 高小尧； 郭琳； 张曼玲；

【Author】 Yong-Feng Feng;Xiao-Yao Gao;Guo Lino;Man-Ling Zhang;School of Automation and Electrical Engineering,Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education,University of Science and Technology Beijing;

【机构】 北京科技大学自动化学院教育部工业过程知识自动化重点实验室；

【摘要】 本文研究了机械臂在模型不确定和外部干扰影响下的轨迹跟踪控制问题。在系统动力学模型未知的情况下,利用模糊逻辑系统逼近不确定部分并采用扰动观测器补偿系统中的未知扰动,设计出基于状态反馈的模糊自适应控制器。该方法可在线调整参数并且不需要精确的系统模型和先验知识。利用李雅普诺夫定理证明了所提出的控制策略可以使闭环系统误差信号半全局一致有界,仿真结果验证了该控制策略的有效性和适用性。更多还原

【Abstract】 In this paper, the trajectory tracking control of a manipulator with model uncertainty and external disturbances is studied. When the dynamic model of the system is unknown, a fuzzy adaptive controller based on state feedback is designed by using the fuzzy logic system to approximate the uncertain part and using the disturbance observer to compensate the unknown disturbance in the system. This method can adjust the parameters online and does not need accurate system model and prior knowledge. The Lyapunov theorem is used to prove that the proposed control strategy can make the error signal of the closed-loop system semi globally uniformly bounded, and the tracking error converges to a very small zero region by adjusting the parameters. The simulation results of a two link manipulator show the effectiveness and applicability of the control strategy.更多还原