Robust distributed model predictive control
By Arthur G. Richards, Jonathan P. How. International Journal of Control, 2007
351 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/42e103274e90a6441ea6ddf45c0e44d16e5f91e0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- David Q. Mayne
- Riccardo Scattolini
- Shengbo Eben Li
- Keqiang Li
- Yang Zheng
- Alexey S. Matveev
- Michael Hoy
- Andrey V. Savkin
In Molecular Biology
- Alexey S. Matveev
- Michael Hoy
- Andrey V. Savkin
- Riccardo Scattolini
- Shengbo Eben Li
- David Q. Mayne
- Francesco Borrelli
Citations in the corpus
- Model predictive control: Recent developments and future promise (2014, background): “In Müller, Reble, and Allgöwer (2012) the problem considered is cooperative control of a set of decoupled nonlinear subsystems; as in Richards and How (2007), the subproblems are solved in sequence at each sample time.”
- Distributed Model Predictive Control for Heterogeneous Vehicle Platoons Under Unidirectional Topologies (2016, background): “Besides, the coupling constraints for collision avoidance in multiagent systems [18], [30] are not considered in problem Fi , which deserves further research.”
- Architectures for distributed and hierarchical Model Predictive Control - A review (2009, background): “The problem considered in [89] consists of controlling a number of disturbed subsystems described by discrete-time linear models with independent dynamics but with coupling constraints.”
- Distributed model predictive control: A tutorial review and future research directions (2013, neutral): “The key feature of cooperative DMPC is that in each of the local controllers, the same global cost function is optimized In recent years, many efforts have been made to develop cooperative DMPC for linear and nonlinear systems strategy: Based on all the input trajectories, each controller c c ← c k…”
- Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey (2014, background): “It is useful as it combines path planning with on-line stability and convergence guarantees, see, e.g., [187, 224].”