Comparative Analysis of Distributed Model Predictive Control Strategies

In this paper, a comparative analysis of two distributed model predictive control (DMPC) strategies tested in simulation on the same test bench in a multiple-agent framework is proposed. Firstly, some details about the non-cooperative DMPC with state-space ‘velocity-form’ formulation called DMPCss are given. After that, the non-cooperative DMPC with input-output model denoted DMPCio is briefly presented. Moreover, the distributed strategies are evaluated with respect to the centralized and decentralized model predictive control (MPC) strategies with ‘velocity-form’ formulation, denoted C-MPCss and DC-MPCss, respectively. The simulation results obtained on the octuple tank process, defined as two quadruple tank processes coupled in series, show that the two non-cooperative algorithms perform similarly with the centralized and decentralized strategies when tuned properly.

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