State-space design of multivariable self-tuning regulators

Abstract

Abstract A state-space design for a multivariable, self-tuning regulator is presented which is based upon eigenvalue assignment. The parameters of a MIMO stochastic process are estimated at each time interval by recursive least squares, and are used to construct an equivalent state-space representation. Eigenvalue assignment of the closed-loop system is accomplished by state feedback, where the state estimate is obtained from the output of a full-order Luenberger observer. The algorithm can be used to regulate non-minimum phase and open-loop unstable systems. Three examples are given.