Abstract
Distributed model predictive control refers to a class of predictive control architectures in which a number of local controllers manipulate a subset of inputs to control a subset of outputs (states) composing the overall system. Different levels of communication and (non)cooperation exist, although in general the most compelling properties can be established only for cooperative schemes, those in which all local controllers optimize local inputs to minimize the same plantwide objective function. Starting from state-feedback algorithms for constrained linear systems, extensions are discussed to cover output feedback, reference target tracking, and nonlinear systems. An outlook of future directions is finally presented.
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© 2013 Springer-Verlag London
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Pannocchia, G. (2013). Distributed Model Predictive Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_5-1
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_5-1
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Publisher Name: Springer, London
Online ISBN: 978-1-4471-5102-9
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Latest
Distributed Model Predictive Control- Published:
- 10 September 2019
DOI: https://doi.org/10.1007/978-1-4471-5102-9_5-2
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Original
Distributed Model Predictive Control- Published:
- 06 March 2014
DOI: https://doi.org/10.1007/978-1-4471-5102-9_5-1