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Hybrid state-space self-tuning control using dual-rate sampling

 

作者: Leang S.Shieh,   Xiao M.Zhao,   John W.Sunkel,  

 

期刊: IEE Proceedings D (Control Theory and Applications)  (IET Available online 1991)
卷期: Volume 138, issue 1  

页码: 50-58

 

年代: 1991

 

DOI:10.1049/ip-d.1991.0007

 

出版商: IEE

 

数据来源: IET

 

摘要:

This paper presents a hybrid state-space self-tuning control scheme using dual-rate sampling for suboptimal digital adaptive control of linear time-invariant continuous-time multi-variable stochastic systems with unknown parameters. An equivalent fast-rate discrete-time state-space innovation model (with estimated states) of the continuous-time system is constructed by using the estimated system parameters and Kalman gain. To utilise the existing optimal regional-pole assignment method developed in the continuous-time domain, the constructed fast-rate discrete-time model is converted into an equivalent continuous-time model for the development of a state-feedback optimal control law with pole placement in a specific region. The developed analogue optimal control law is then converted into an equivalent pseudo-slow-rate digital control law via the proposed digital redesign technique, which can be realised via slow-rate digital electronics. The proposed method enables the development of a digitally implementable advanced control algorithm for digital adaptive control of continuous-time multivariable stochastic systems which may be unstable and/or have nonminimum phase.

 

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