Entropy Based Indirect Iterative Learning Control for Robot Manipulator with Random Disturbances
A novel entropy based indirect iterative learning control(ILC)methodology for robotic manipulator with random dis-turbance is developed by combining the minimum error entropy and the optimal strategy,which is used to update local controller parameters between any two adjacent batches.Moreover,Entropy is a uni fied probabilistic measure of uncertainty quanti fication whether the random disturbances are Gaussian or not.An innovative performance index that formulates the relation between the entropy of error and controller gains is proposed.Then the nonlinear optimal method to obtain new gains is presented ,and stability is analysized.Finally,the effectiveness and feasibility of the proposed control schemes is veri fied by some simulation results.
CHEN Haiyong WANG Liwei XING Guansheng SUN Hexu
School of Control Sciences and Engineering Hebei University of Technology,Tianjin 300130,P.R.China
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-6
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）