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作者机构:[a]Department of Electrical and Computer Engineering University of Michigan Dearborn MI 48128 U.S.A.
出 版 物:《AUTOMATICA》 (自动学)
年 卷 期:1994年第30卷第12期
页 面:1999-2007页
核心收录:
学科分类:0711[理学-系统科学] 0808[工学-电气工程] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0701[理学-数学] 071101[理学-系统理论]
主 题:ADAPTIVE CONTROL SELF-TUNING CONTROL COMPUTER CONTROLLED SYSTEM STOCHASTIC SYSTEM ESTIMATION ALGORITHM STATE FEEDBACK
摘 要:A state space based dual-rate self-tuning algorithm is proposed for the case where the output sampling rate is slower than the input update rate, A state space innovation model suitable for dual-rate self-tuning control is derived. The parameters of the innovation model together with the states are estimated by a recursive prediction error estimator. The control strategy has been based on a pole restriction principle. Simulation studies are presented to establish the practical usefulness of the algorithm.