Output feedback model predictive control for nonlinear systems

In this paper, an Output Feedback Model Predictive Control for nonlinear systems is presented. The proposed output feedback control consists of the well known robust controller NCGPC (Nonlinear Continuous Time Generalized Predictive Control) and an open loop observer (a simulated model in parallel) in order to estimate the output derivatives and a regulation filter used to account for plant/model mismatch. The main advantages of the new approach are i) that the assumption of full-state feedback inherent in feedback linearization schemes is eliminated, the only measurement required is the output and finally ii) the process output converges to a constant reference in spite of presence of parameter uncertainties and process disturbances. The analysis of the induction motor and simulation results in the numerical example show that the output feedback model predictive control proposed can tolerate certain process uncertainty.

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