A new model reference control architecture for uncertain dynamical systems

Here, a model reference control design is applied to uncertain dynamical systems. The design approach and related theory is inspired by both robust control and previous work in model reference adaptive control. The result is a simple (non-adaptive) control system with important performance guarantees against a general and uncertain dynamics. Similar to the design of adaptive controllers, we assume the existence of a parameterization of the system uncertainty. It is shown by using a recently proposed command governor architecture that if a priori knowledge of a conservative upper bound on the unknown ideal weight matrix is available, then it is possible not only to stabilize the uncertain dynamical system but also to achieve a guaranteed performance. Specifically, we show the controlled uncertain dynamical system approximates a given ideal reference system by properly choosing the design parameter of a command governor. Numerical examples illustrate the effectiveness of the proposed methodology.