自动化学报2008，Vol.34Issue(4)：426-432,7.
非线性大系统的跟踪具有不同幅值轨线的分散型迭代学习控制器
Decentralized Iterative Learning Controllers for Nonlinear Large-scale Systems to Track Trajectories with Different Magnitudes
摘要
Abstract
In hierarchical steady-state optimization programming for large-scale industrial processes, a feasible technique is to use information of the real system so as to modify the model-based optimum. In this circumstance, a sequence of step function-type control decisions with distinct magnitudes is computed, by which the real system is stimulated consecutively. In this paper, a set of iterative learning controllers is embedded into the procedure of hierarchical steady-state optimization in decentralized mode for a class of large-scale nonlinear industrial processes. The controller for each subsystem is used to generate a sequence of upgraded control signals so as to take responsibilities of the sequential step control decisions with distinct scales. The aim of the learning control design is to consecutively refine the transient performance of the system. By means of the Hausdorff-Young inequality of convolution integral, the convergence of the updating rule is analyzed in the sense of Lebesgne-p norm. Invention of the nonlinearity and the interaction on convergence are discussed. Validity and effectiveness of the proposed control scheme are manifested by some simulations.关键词
Nonlinear large-scale systems, steady-state optimization, iterative learning control, Lebesgue-p norm, convergenceKey words
Nonlinear large-scale systems, steady-state optimization, iterative learning control, Lebesgue-p norm, convergence分类
信息技术与安全科学引用本文复制引用
阮小娥,陈凤敏,万百五..非线性大系统的跟踪具有不同幅值轨线的分散型迭代学习控制器[J].自动化学报,2008,34(4):426-432,7.基金项目
Supported by National Natural Science Foundation of China(F030101-60574021) and National "985" Project of China Executedin Xi'an Jiaotong University （F030101-60574021）
