Prior knowledge in model reference adaptive control of multi-input multi-output systems

This paper shows how the prior knowledge necessary for model reference adaptive control of multi-input multi-output systems can be weakened. In particular, it is shown that the real variables appearing in the system interactor matrix can be estimated along with the other parameters in the system model. A theoretical convergence analysis of the resulting algorithm is presented together with simulation results.