Originally, adaptivecontrol theory was developed for the ideal system models, i.e., linear system models under the assumption that relative degree and upper bounds on the order of the systems are known. At the beginn...
详细信息
Originally, adaptivecontrol theory was developed for the ideal system models, i.e., linear system models under the assumption that relative degree and upper bounds on the order of the systems are known. At the beginning of the last decade, adaptivecontrolalgorithms designed for such ideal system models were strongly attacked by many researchers due to ''lack of robustness'' in the presence of unmodeled dynamics and external disturbances. The purpose of the present paper is to relax existing constant pressure on the adaptivecontrolalgorithms originally designed for the ideal system models. It is shown that such adaptivecontrolalgorithms are globally stable and robust with respect to unmodeled dynamics and external disturbances without any modifications, such as isigma-modification, epsilon1-modification, relative dead-zone, projection of the parameter estimates, etc. Global stability of the unmodifiedalgorithms is established by requiring the reference signal to be persistently exciting.
暂无评论