Arbitrarily Fast Multivariable Least-squares MRAC
Abstract
A novel least-squares model-reference direct adaptive control (LS-MRAC) algorithm for multivariable (MIMO) plants is presented. The controller parameters are directly updated based on the output tracking error. The control law is crucially modified to reduce the relative degree of the error model to zero. A complete Lyapunov-based stability analysis as well as a tracking error convergence characterization is provided demonstrating that the LS-MRAC can achieve arbitrarily fast tracking while maintaining satisfactory parameter convergence for appropriate adaptation gains. Simulation results show a significant improvement in tracking performance compared to previous methods.
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