Designing of non-fragile robust model predictive control for constrained uncertain systems and its application in process control |
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Affiliation: | 1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China;2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore;3. Temasek Laboratories, National University of Singapore, Singapore 117508, Singapore;4. Beijing Engineering Research Center of Industrial Spectrum Imaging, Beijing 100083, China |
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Abstract: | A non-fragile robust model predictive control (RMPC) is designed in the uncertain systems under bounded control signals. To this aim, a class of the nonlinear systems with additive uncertainty is considered in its general form. The RMPC synthesis could lead to the proper selection of the controller’s gains. Thus, the non-fragile RMPC design is translated into a minimization problem subjected to some constraints in terms of linear matrix inequality (LMI). Hence, the controller’s gains are computed by solving such a minimization problem. In some numerical examples, the suggested non-fragile RMPC is compared with the other methods. The simulation results demonstrate the effectiveness of the proposed RMPC in comparison with similar techniques. |
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Keywords: | Non-fragile controller design Robust model predictive control (RMPC) Uncertain systems Stability analysis |
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