Contractive model predictive control for constrained nonlinear systems

By S. L. Kothare, Manfred Morari. IEEE Transactions on Automatic Control, 2000

347 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/4e3942d635b7f7bc6532aee3512e1d24b0dc2b63

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In Cardiology and Cardiovascular Medicine

In Control and Systems Engineering

Citations in the corpus

Output feedback stabilization of constrained systems with nonlinear predictive control (2003, methodology): “Another possibility to avoid explicit information on H 1 is to rewrite the observer equations in terms of the original co-ordinates as proposed in References [14, 27].”
Stabilization of nonlinear systems with state and control constraints using Lyapunov-based predictive control (2005, positive): “Remark 1: Lyapunov-based predictive control approaches (see, for example, [13] , [20]) typically incorporate a Lyapunov function decay constraint similar to that of Eq.9 , albeit requiring the constraint to hold at the end of the prediction horizon as opposed to during the first time step.”
Lyapunov-Based Model Predictive Control of Nonlinear Systems Subject to Data Losses (2008, methodology): “We consider a Lyapunov-based model predictive control (LMPC) scheme [33]–[35] (see also [36], [37]) based on uniting receding”
Learning Model Predictive Control for Iterative Tasks. A Data-Driven Control Framework (2016, neutral): “This is the case of the vast majority of seminal papers on MPC [17], [34]–[36].”
Nonlinear Model Predictive Control for the Swing-Up of a Rotary Inverted Pendulum (2004, background): “MPC was first proposed for linear systems [1, 2] and later extended to nonlinear systems (called NMPC) [3–8].”
Robust predictive control of switched systems: Satisfying uncertain schedules subject to state and control constraints (2008, methodology): “One such control method is model predictive control (MPC), which has been studied extensively in the context of purely continuous and purely discrete time linear and nonlinear systems (see, for example, [16–20] and the survey paper, [21]).”
An Introduction to Nonlinear Model Predictive Control (2002, background): “Different possibilities to achieve closed-loop stability for NMPC using a finite horizon length have been proposed, see for example [3, 17, 20, 23 , 34, 35, 38, 39, 44, 51, 53, 55, 56, 60, 62, 63, 70].”
Stability and Robustness of Nonlinear Receding Horizon Control (2000, methodology): “The contractive constraint method has also been studied in a purely RH setting in [18], [31] where continuous systems subject to sampled-data control are considered.”
Hybrid predictive control of nonlinear systems: method and applications to chemical processes (2004, background): “see References [2–8]) that focus on the issues of stability, constraint satisfaction and performance optimization for nonlinear systems.”
Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics (2009, methodology): “The control scheme is inspired by the MPC technique proposed in [20], where a “contractive” constraint is imposed on the state to guarantee stability.”