Results obtained previously on the stability of adaptive predictive control systems are generalized by reducing the requirements for stability to a single condition that is applicable to linear discrete processes with disturbances and unmodeled plant dynamics. 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.
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