Abstract
Abstract An algorithm is proposed for combined identification and control of linear discrete time multivariable systems. This algorithm is an extension of a recently proposed algorithm to handle the case where process noise is assumed to perturb the system dynamics. The modified algorithm uses a canonical innovation representation of the system where the parameters of the system matrices and the Kalman filter gain matrix are estimated with a normalized stochastic approximation algorithm. The combined problem is solved in a bootstrap manner in three separate stages; parameter identification, state estimation, and control. The proposed algorithm is computationally simple which makes it suitable for on-line applications.
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