Research on Improvement of Model-free Learning Adaptive Controller Based on Multi-innovation Theory

摘要：

To improve the convergence rate of model-free learning adaptive controller (MFLAC). A new design method of MFLAC is presented in this paper. We extend the model-free control law from signal innovation form to multi-innovation form based on the multi-innovation theory and the parameters are optimized by artificial fish swarm algorithm (AFSA).The performance analysis and simulation results show that the proposed model-free controller based on multi-innovation has faster convergence rate and better tracking performance.

关键词： model-free multi-innovation artificial fish swarm algorithm

作者: Yu Hua-bing Qin Pin-le

作者单位: School of Chemical Engineering and Environment North University of China Tai Yuan City, ShanXi Provi School of Electronics and Computer Science and Technology North University of China Tai Yuan City, S

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 14-18

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）