信息与控制2011，Vol.40Issue(6)：772-776,5.DOI:10.3724/SP.J.1219.2011.00772
非线性系统迭代跟踪控制的批次遗忘学习算法
Forgetting Learning Algorithm with Batches for Iterative Tracking Control of Nonlinear Systems
摘要
Abstract
As the P-type iterative learning control algorithm is sensitive to the initial error and the output error disturbance, and the PD-type iterative learning control algorithm can easily amplify the noise and reduce the robustness of the system, a PD-type iterative learning tracking control algorithm for repetitive nonlinear time-varying systems with any desired output and bounded disturbances is investigated. By using the desired trajectory, the desired control and tracking error expectations memorized in the process of iterative learning, the learning controller is designed based on the variable batches of forgetting factors. Based on the X norm theory and the Bellman-Gronwall inequality, the necessary and sufficient conditions for the existence of the learning gain are discussed, and the uniform convergence of the control algorithm is analyzed to ensure that the batch error of the closed-loop tracking system is bounded. The robustness and the dynamic performance of the system are improved by the algorithm. Simulation on the tracking control of the single-joint robot arm illustrates the effectiveness of the proposed method.关键词
迭代学习控制/非线性系统/遗忘因子/跟踪控制/收敛性分析Key words
iterative learning control/ nonlinear system/ forgetting factor/ tracking control/ convergence analysis分类
信息技术与安全科学引用本文复制引用
陶洪峰,丁保,杨慧中..非线性系统迭代跟踪控制的批次遗忘学习算法[J].信息与控制,2011,40(6):772-776,5.基金项目
国家自然科学基金资助项目(60674092) （60674092）
上海市科学技术委员会资助项目(09DZ2273400) （09DZ2273400）
中央高校基本科研业务费专项资金资助项目(JUSRP 111 A47). （JUSRP 111 A47）
