Observations-weighted controllers for linear stochastic systems using a dual criterion: the multivariable case

Abstract

The solution of a dual criterion observations-weighted control problem is obtained, using the polynomial equation approach, for linear, stochastic, multivariable, discrete-time systems. The system model involves input disturbance, and reference and coloured measurement noise signals. The dual criterion considered here includes the sensitivity functions in addition to the usual observations-weighted cost function. It is shown that the observations-weighted controller presented guarantees the internal stability of the closed-loop system, even in a light control for non-minimum-phase plants, whenever the sensitivity and/or complementary sensitivity weighting matrices are non-zero. The controller is also effective for improving the robustness of the usual observations-weighted controller, but has comparable computation loads to the dual criterion linear quadratic gaussian (LQG) controller in a general situation.

Additional information

Notes on contributors

KEIGO WATANABE†

†This work was carried out while the author was an Invited Research Fellow at the Division of Computer Science of the National Technical University of Athens,Greece.