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We present a computational study of a discrete-time adaptive control algorithm that is eective for multi-input, multi-output systems that are either minimum phase or nonminimum phase. The adaptive control algorithm requires limited model information, specically, the rst nonzero Markov parameter and the nonminimum-phase transmission zeros of the transfer function from the control signal to the performance measurement. Furthermore, the adaptive control algorithm is eective for stabilization, command following, and disturbance rejection. For command following and disturbance rejection, the algorithm does not require knowledge of the command or disturbance spectrum. We explore computationally the algorithm’s performance and robustness in the presence of errors in the required modeling information.

A Computational Study of the Performance and Robustness Properties of Retrospective Cost Adaptive Control