Abstract
In the previous chapters, full state feedback is assumed in the EMPC designs. This assumption is typically not satisfied in practical applications. In this chapter, two output feedback-based EMPC schemes with guaranteed closed-loop stability properties are presented. In the first scheme, a high-gain observer-based EMPC for the class of full-state feedback linearizable nonlinear systems is introduced. A high-gain observer is used to estimate the nonlinear system state using process output measurements. To achieve fast convergence of the state estimate to the actual system state as well as to improve the robustness of the estimator to measurement and process noise, a high-gain observer and a robust moving horizon estimation (RMHE) scheme are used to estimate the system states in the second output feedback-based EMPC. In particular, the high-gain observer is first applied for a small time period with continuous output measurements to drive the estimation error to a small value. Once the estimation error has converged to a small neighborhood of the origin, the RMHE is activated to provide more accurate and smoother state estimates. The two EMPC schemes are applied to a chemical process example to demonstrate the applicability and effectiveness of the schemes.
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Ellis, M., Liu, J., Christofides, P.D. (2017). State Estimation and EMPC. In: Economic Model Predictive Control. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-41108-8_5
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DOI: https://doi.org/10.1007/978-3-319-41108-8_5
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