Stable Weighted Multiple Model Adaptive Control of Continuous-Time Plant With Large Parameter Uncertainties

This paper presents a weighted multiple model adaptive control (WMMAC) scheme to deal with large parametric uncertainty of continuous-time plant. In this proposed scheme, each ‘local’ controller is designed according to the mixed- $\mu $ -synthesis method to consider small uncertainty of plant parameters and disturbance; the weighting algorithm is directly based on model output errors rather than the residuals generated by multiple Kalman filters as in classical multiple model adaptive control (CMMAC). The closed-loop stability (signal boundedness) and tracking performance of the proposed WMMAC system are proved with the help of virtual equivalent system (VES) concept and methodology.

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