A Linear Fractional Transformation Based Approach To Robust Model Predictive Control Design In Uncertain Systems

IEEE ACCESS(2020)

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摘要
A novel robust model predictive control (RMPC) scheme is developed for uncertain nonlinear systems. To the RMPC design, firstly, the uncertain system would be described using a linear fractional transformation (LFT). Then, regarding the system's uncertainties and control limitations, a linear matrix inequality (LMI) based control strategy is addressed to translate the RMPC synthesis into a minimization problem. Thus the controller's gains are automatically updated at some time-instants by the solution of such optimization problem. Finally, the outcomes are numerically applied in some control examples. The simulation results show the effectiveness of the suggested robust predictive controller in comparison to similar RMPC techniques.
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关键词
Uncertain systems, Uncertainty, Linear matrix inequalities, Predictive control, Optimization, Nonlinear systems, Mathematical model, Linear fractional transformation, linear matrix inequality, robust model predictive control, uncertain systems
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