ADAPTIVE TRACKING OF A CLASS OF FIRST-ORDER SYSTEMS WITH BINARY-VALUED OBSERVATIONS AND FIXED THRESHOLDS

作     者：Jin GUO Ji-Feng ZHANG Yanlong ZHAO 

作者机构：Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences 

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.60934006  61174042 and 61120106011 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2012年第25卷第6期

页      码：1041-1051页

摘      要：This paper considers the adaptive tracking problem for a class of first-order systems with binary-valued observations generated via fixed thresholds. A recursive projection algorithm is proposed for parameter estimation based on the statistical properties of the system noise. Then, an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectations of the innovation and output prediction with respect to the estimates, the closed-loop system is shown to be stable and asymptotically optimal. Meanwhile, the parameter estimate is proved to be both almost surely and mean square convergent, and the convergence rate of the estimation error is also obtained. A numerical example is given to demonstrate the efficiency of the adaptive control law.

主 题 词：Adaptive control binary-valued observation optimal tracking parameter estimation,stochastic system. 

学科分类：02[经济学] 0202[经济学-财政学类] 020208[020208] 07[理学] 0714[0714] 070103[070103] 0701[理学-数学类] 

核心收录：

D　O　I：10.1007/s11424-012-1257-0

馆 藏 号：203434879...