Model-free learning adaptive control for nonlinear systems with multiple time delays
Author(s): HU Zhi-qiang, LI Xiang-dong
Pages: 261-264
Year: 2001 Issue: 2
Journal: JOURNAL OF HARBIN INSTTTUTE OF TECHNOLOGY
Keyword: 非线性系统; 无模型学习自适应控制; 参数自适应预报; 增量型最小化递推预测模型; 参数限定长度; 动态线性化;
Abstract: Presents the model-free learning adaptive control and its parameter adaptive predicting with parameter control length for a class of nonlinear discrete-time systems with multiple time delays based on dynamic approximate linearization increment minimized model and recursive predicting model method and the use of model-free learning adaptive control for nonlinear systems with heavy multiple time delays, and points out that there is no need for structural information, mathematical model, external testing signals, training process, Diophantine equation's solution and matrix operations, little on-line compution, excellent real-time, and design only by using L/O data of the controlled systems, and no unmodelled dynamics at all, and concludes from simulation results that several typical nonlinear systems given to demonstrate the correctness and effectiveness of the approach proposed.
Pages: 261-264
Year: 2001 Issue: 2
Journal: JOURNAL OF HARBIN INSTTTUTE OF TECHNOLOGY
Keyword: 非线性系统; 无模型学习自适应控制; 参数自适应预报; 增量型最小化递推预测模型; 参数限定长度; 动态线性化;
Abstract: Presents the model-free learning adaptive control and its parameter adaptive predicting with parameter control length for a class of nonlinear discrete-time systems with multiple time delays based on dynamic approximate linearization increment minimized model and recursive predicting model method and the use of model-free learning adaptive control for nonlinear systems with heavy multiple time delays, and points out that there is no need for structural information, mathematical model, external testing signals, training process, Diophantine equation's solution and matrix operations, little on-line compution, excellent real-time, and design only by using L/O data of the controlled systems, and no unmodelled dynamics at all, and concludes from simulation results that several typical nonlinear systems given to demonstrate the correctness and effectiveness of the approach proposed.
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