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Fast suboptimal state-space self-tuner for linear stochastic multivariable systems

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3 Author(s)
Shieh, L.S. ; University of Houston, Department of Electrical Engineering, Houston, USA ; Wang, C.T. ; Tsay, Y.T.

A fast state-space self-tuner is developed for suboptimal control of linear stochastic multivariable systems. The suboptimal self-tuner is determined by utilising both the standard recursive-extended-least-squares parameter estimation algorithm and the recently developed matrix sign algorithm, which gives a fast solution of the steady-state discrete Riccati equation. The developed suboptimal state-space self-tuner can be applied to a class of stable/unstable and minimum/non-minimum phase linear stochastic multivariable systems, in which the pair (A, C) is block observable and the pair (A, B) is stablisable. Also, the pair (A, Q¿¿) with Q¿¿Q¿¿T = Q is detectable where A, B and C are system, input and output matrices, respectively, and Q is a weighting matrix in a quadratic performance index.

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Control Theory and Applications, IEE Proceedings D  (Volume:130 ,  Issue: 4 )