Receding horizon control of nonlinear systems

Michalska, H.

doi:10.1109/cdc.1988.194354

Cited by 85 publications

(98 citation statements)

References 4 publications

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“…In what follows we sketch an approximation method for the solution of (2.1)-(2.2), based on model predictive control (MPC), which furnishes a suboptimal control by an iterative solution over a sequence of finite time steps, but, nonetheless, it allows an explicit representation of the control strategy [6,35,81,80].…”

Section: Model Predictive Control Of the Microscopic Dynamicsmentioning

confidence: 99%

Recent Advances in Opinion Modeling: Control and Social Influence

Albi

Pareschi

Toscani

et al. 2017

Modeling and Simulation in Science, Engineering and Technology

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We survey some recent developments on the mathematical modeling of opinion dynamics. After an introduction on opinion modeling through interacting multi-agent systems described by partial differential equations of kinetic type, we focus our attention on two major advancements: optimal control of opinion formation and influence of additional social aspects, like conviction and number of connections in social networks, which modify the agents' role in the opinion exchange process. PreliminariesWe introduce some of the essential literature on the opinion formation, by emphasizing the role of the kinetic description. New problems recently treated in the scientific community are outlined. Then, the mathematical description of the core ideas of kinetic models for opinion formation are presented in details.

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Section: Model Predictive Control Of the Microscopic Dynamicsmentioning

confidence: 99%

Recent Advances in Opinion Modeling: Control and Social Influence

Albi

Pareschi

Toscani

et al. 2017

Modeling and Simulation in Science, Engineering and Technology

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“…Several NMPC concepts that guarantee stability and that are similar to this setup have been proposed (Mayne and Michalska, 1990;Chen and Allgöwer, 1998;Jadbabaie et al, 1999a), see (Mayne et al, 2000) for a review. Similar results have also been obtained for the discrete time case (Meadows and Rawlings, 1993;De Nicolao et al, 1996;Findeisen, 1997).…”

Section: Nonlinear Mpc State Feedbackmentioning

confidence: 99%

On output feedback nonlinear model predictive control using high gain observers for a class of systems

Imsland

Findeisen

Bullinger³

et al. 2001

IFAC Proceedings Volumes

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In recent years, nonlinear model predictive control schemes have been derived that guarantee stability of the closed loop under the assumption of full state information. However, only limited advances have been made with respect to output feedback in connection to nonlinear predictive control. Most of the existing approaches for output feedback nonlinear model predictive control do only guarantee local stability. Here we consider the combination of stabilizing instantaneous NMPC schemes with high gain observers. For a special MIMO system class we show that the closed loop is asymptotically stable, and that the output feedback NMPC scheme recovers the performance of the state feedback in the sense that the region of attraction and the trajectories of the state feedback scheme are recovered for a high gain observer with large enough gain and thus leading to semi-global/non-local results.

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“…Receding horizon techniques have proved to be effective numerically both for optimal control problems governed by ordinary (e.g. [3,[11][12][13]15,16]) and for partial differential equations, e.g. in the form of the instantaneous control technique for problems in fluid mechanics [2,4,5,9].…”

Section: Introductionmentioning

confidence: 99%

Receding horizon optimal control for infinite dimensional systems

Ito

Kunisch

2002

ESAIM: COCV

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Abstract. The receding horizon control strategy for dynamical systems posed in infinite dimensional spaces is analysed. Its stabilising property is verified provided control Lyapunov functionals are used as terminal penalty functions. For closed loop dissipative systems the terminal penalty can be chosen as quadratic functional. Applications to the Navier-Stokes equations, semilinear wave equations and reaction diffusion systems are given.Mathematics Subject Classification. 49L15, 49N35, 93C20, 93Dx.

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Receding horizon control of nonlinear systems

Cited by 85 publications

References 4 publications

Recent Advances in Opinion Modeling: Control and Social Influence

Recent Advances in Opinion Modeling: Control and Social Influence

On output feedback nonlinear model predictive control using high gain observers for a class of systems

Receding horizon optimal control for infinite dimensional systems

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