Model reference adaptive control for exponentially convergent systems with input and output constraints

This paper shows that the standard stochastic model reference adaptive control algorithm can be applied without change to the time-varying systems whose parameters converge exponentially. Moreover, it is shown that a system with constraints on amplitude as well as on the rate of change of input and output signals can be implemented by using a time-varying reference model. The resulting closed-loop system is globally asymptotically stable, provided that the reference model remains stable. An example that demonstrates the performance of this algorithm is the biological control system for blood pressure stabilization.