FUNCTIONAL PERSISTENCE OF EXCITATION AND OBSERVABILITY FOR LEARNING CONTROL-SYSTEMS

作     者：MOORE, JB HOROWITZ, R MESSNER, W 

作者机构：UNIV CALIF BERKELEYDEPT MECH ENGNBERKELEYCA 94720 

出 版 物：《JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME》 (美国机械工程师学会汇刊: 动力系统、测量与控制杂志)

年 卷 期：1992年第114卷第3期

页      面：500-507页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0804[工学-仪器科学与技术] 0811[工学-控制科学与工程] 

主　　题：Errors Stability Excitation Control algorithms Control systems Integral equations Linear systems 

摘      要：Adaptive systems involving function learning can be formulated in terms of integral equations of the first kind, possibly with separable, finite-dimensional kernels. The learning process involves estimating the influence functions (Messner et al., 1989). To achieve convergence of the influence function estimates and exponentially stability, it is important to have persistence of excitation in the training tasks. This paper develops the concept of functional persistence of excitation (PE), and the associated concept of functional uniform complete observability (UCO). Relevant PE and UCO properties for linear systems are developed. For example, a key result is that uniform complete observability in this context is maintained under bounded integral operator output injection-a natural generalization of the corresponding finite dimensional result. This paper also demonstrates the application of the theory to linear error equations associated with a repetitive control algorithm.