Sequential distributed model predictive control for state-dependent nonlinear systems
Abokhatwa, Salah G. and Katebi, Reza; (2013) Sequential distributed model predictive control for state-dependent nonlinear systems. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, GBR, pp. 565-570. ISBN 9780769551548 (https://doi.org/10.1109/SMC.2013.102)
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In this paper, sequential nonlinear Distributed Model Predictive Control (DMPC) algorithms for large-scale systems that can handle constraints are proposed. The proposed algorithms are based on nonlinear MPC strategy, which uses a statedependent nonlinear model to avoid the complexity of the nonlinear programming (NLP) problem. In this distributed framework, local MPCs solve convex optimization problem and exchange information via one directional communication channel at each sampling time to achieve the global control objectives of the system. Numerical simulation results show that the performance of the proposed DMPC algorithms is close to the centralized NMPC but computationally more efficient compared to the centralized one.
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Item type: Book Section ID code: 48000 Dates: DateEvent1 December 2013PublishedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
University of Strathclyde > University of StrathclydeDepositing user: Pure Administrator Date deposited: 12 May 2014 11:27 Last modified: 08 Apr 2024 13:09 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/48000