Switched State Model Predictive Control of Fractional‐Order Nonlinear Discrete‐Time Systems

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Abstract
Model predictive control is one of the more effective and frequently employed‐in‐industry control methods, especially for multiple input multiple output (MIMO) processes, in which a dynamic model of the process is used to predict its behavior over some time horizon and to determine the optimal future control policy. In this paper, a novel predictive algorithm for advanced process control for nonlinear and/or uncertain fractional‐order discrete‐time processes is proposed. First, a state model predictive controller forMIMOlinear fractional‐order discrete‐time systems is introduced, and then the concept is extended toMIMOnonlinear and uncertain fractional‐order processes which can be modeled by means of linear multimodels of fractional order. The algorithm is based on fast model selection to cope with process uncertainty and represents a class of so‐called switched systems. Finally, a simulation example is provided.

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