Multivariable adaptive control: identifiable parameterizations and parameter convergence

The paper presents a direct model reference adaptive control algorithm for multivariable systems that has guaranteed parameter convergence properties. The algorithm requires fewer parameters than existing schemes, and the parameters converge to their nominal values under persistency of excitation conditions. Simple frequency domain conditions on the external inputs are derived to satisfy these conditions. The convergence of the controller parameters to their nominal values guarantees a certain degree of robustness of the algorithms and ensures that the model matching objective is satisfied asymptotically