Decentralized receding horizon control for large scale dynamically decoupled systems

By Tamás Keviczky, Francesco Borrelli, G. Balas. at - Automatisierungstechnik, 2009

448 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/40b90c79fb9fb9f91467b7866f74a5885402d5d6

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In Computer Networks and Communications

In Control and Systems Engineering

Citations in the corpus

Distributed optimal control of multiple systems (2010, background): “Different distributed receding horizon control laws have been proposed in Dunbar and Murray (2006), Keviczky, Borrelli, and Balas (2006), Camponogara and Talukdar (2007) and Ferrari-Trecate, Galbusera, Marciandi, and Scattolini (2009).”
Distributed model predictive control: A tutorial review and future research directions (2013, unknown): “of Khan and Moura (2008), Stanković, Stanković, and Stipanović (2009a, 2009b) and in Vadigepalli and Doyle (2003), where an all-to-all communication among subsystems was required.”
Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics (2009, background): “Stabilizing MPC algorithms for decentralized and distribu ted systems have been proposed in [10], [11], [12], [13], [14], [ 15], [16] for dynamically coupled and decoupled systems.”
A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems (2017, background): “Great effort has been devoted to investigating this highly complex problem for special types of systems, including spatially distributed systems [147]–[151], dynamically decoupled systems [152], [153], weakly coupled systems [154], and strongly connected systems [155].”
Robust distributed model predictive control (2007, background): “Dunbar and Murray 2006), partial grouping of computations (Keviczky et al. 2006), loitering options for safety guarantees (Schouwenaars et al.”
Architectures for distributed and hierarchical Model Predictive Control - A review (2009, background): “In [48,49], any agent (a node of a graph) is described as a discretetime nonlinear system which knows the state of its neighborhoods without delay.”
Distributed LQR Design for Identical Dynamically Decoupled Systems (2008, background): “The philosophy of our approach builds on the recent works [13]–[15], where at each node, the model of its neighbors are used to predict their behavior.”
Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability (2012, background): “Distributed receding horizon control of multiple decoupled vehicles has also been explored for linear [13], [18] and nonlinear [7], [9], [11] vehicle dynamics, with coupling in cost functions and/or constraints.”
Distributed Model Predictive Control for Heterogeneous Vehicle Platoons Under Unidirectional Topologies (2016, methodology): “Note also that many previous works on DMPC assume that all the nodes a priori know the desired set point [14], [27], [28].”