Stable Discrete-Time Adaptive Control in the Presence of Unmodeled Dynamics

This paper generalizes the results obtained previously by the authors on the stability of adaptive predictive control systems by reducing the requirements for stability to a single condition that is applicable to a broad class of deterministic, stochastic and/or time-varying, linear discrete systems with process-model order mismatch. The proposed design approach uses a normalized parameter estimation scheme, which permits a formal proof that the modeling errors can be treated as a bounded disturbance, and a parameter adaptation stopping criterion to guarantee global stability. Simulation results based on a benchmark example, illustrate the theoretical concepts and their practicality.