Model Reference Adaptive Control for Constrained Linear Systems

Pham A. Tu and Kenko Uchida


Model reference adaptive control, State and control constraints


The presence of state and control constraints in physical systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfillment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.

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