动态补偿逆的非线性内模控制在机器人中的应用  

Application of Non-linear Internal Model Control Based on Dynamic Compensation Inverse in Robot

作　　者：郝晓弘[1] 耿亮[1] 麻园园 赵振男 

机构地区：[1]兰州理工大学电气工程与信息工程学院,兰州730050 [2]国投甘肃小三峡发电有限公司,兰州730050

出　　处：《自动化与仪表》2010年第2期39-41,共3页Automation & Instrumentation

基　　金：甘肃省科技攻关项目(GS044-A52-001-24);甘肃省自然科学基金项目资助(3ZS042-B25-012)

摘　　要：针对机器人的非线性不确定性和传统非线性内模控制在控制上存在的不足,提出一种基于动态补偿逆的非线性不确定系统RBF内模控制,在引入RBF建立逆模型的同时,将无模型自适应控制方法作为附加控制器,用于在模型偏离被控对象时在线修正逆模型。仿真结果表明,本文提出的方法不仅对机器人系统的常量摄动具有较好的鲁棒性,对时变不确定性仍能保持较好的跟踪效果,具有较好的实时性、鲁棒性和在线校正功能。Aiming at a method of robot control system for the robot＇s non-linear uncertain systems and the traditional non-linear internal model control in the control deficiencies, this paper introduced a based on dynamic compensation inverse of radial basis function （RBF） internal model control for nonlinear uncertain systems method. At the same time, in the introduction of RBF to establish the inverse model, there is model free adaptive control （MFAC） method as an additional controller. Both forward and backward models will be automatically modified online when they deviate from the plant. The simulation results show that the method proposed in this paper not only to the robot＇s constant perturbation system has good robustness of time-varying uncertainties remain better tracking results, with better real- time performance, robustness, and online calibration.

关 键 词：无模型自适应控制 动态补偿 逆系统方法 内模控制 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]