Nonlinear MPC Versus MPC Using on-Line Linearisation — A Comparative Study

Blet, Nora S. M.; Megías, David; Serrano, Javier; Prada, César de

doi:10.3182/20020721-6-es-1901.00593

Cited by 8 publications

(2 citation statements)

References 8 publications

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“…However, this paper focuses on the last item on the list: Ensure Validity of Predictions in LV-MPC. Although industrial processes are non-linear, most implemented control solutions are based on linear models [11,12]. LV-MPC is based on a linear structure for predictions, thus there is model-process mismatch.…”

Section: Introductionmentioning

confidence: 99%

Latent variable based model predictive control: Ensuring validity of predictions

Lauri

Sanchis

Martínez

et al. 2013

Journal of Process Control

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This paper presents a methodology to constrain the optimization problem in LV-MPC so that validity of predictions can be ascertained. LV-MPC is a model-based predictive control methodology implemented in the space of the latent variables and is based on a linear predictor. Provided real processes are non-linear, there is model-process mismatch, and under tight control, the predictor can be used for extrapolation. Extrapolation leads to bad predictions which deteriorates control performance, hence the interest in validity of predictions. In the proposed approach first two validity indicators on predictions are defined. The novelty in the two indicators proposed is they neglect past data, and so validity of predictions is ascertained in terms of future moves which are actually the degrees of freedom in the optimization. Second, the indicators are introduced in the optimization as constraints. Provided the indicators are quadratic, recursive optimization with linearised constraints is implemented. A MIMO example shows how ensuring validity of predictions neglecting past data can improve closed-loop performance, specially under tight control outside the identification region.

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Section: Introductionmentioning

confidence: 99%

Latent variable based model predictive control: Ensuring validity of predictions

Lauri

Sanchis

Martínez

et al. 2013

Journal of Process Control

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“…Also in Ref. [6] the NMPC is solved at every sampling time as a series of linearized models by QP saving computation time. Other approaches [7] consider the use of piece-wise affine models and multiparametric optimization methods in order to pre-compute off-line a control law that can be applied then on-line as a function of the current values of the state and the control signal.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear parametric predictive control. Application to a continuous stirred tank reactor

Assandri

Prada

Cristea

et al. 2009

Asia-Pacific J Chem Eng

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This paper presents a nonlinear model-based controller based on the ideas of parametric predictive control applied to a continuous stirred tank reactor (CSTR) process unit. Controller design aims at avoiding the complexity of implementation and long computational times associated with conventional NMPC while maintaining the main advantage of taking into account process nonlinearities that are relevant for control. The design of the parametric predictive controller is based on a rather simplified process model having parameters that are instrumental in determining the required changes to the manipulated variables for error reduction. The nonlinear controller is easy to tune and can operate successfully over a wide range of operating conditions. The use of an estimator of unmeasured disturbances and process-model mismatch further enhances the behavior of the controller. 

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LTI-MPC for the Micro-grid Control

Vidyasagar

2023

Springer Tracts in Electrical and Electronics Engineering

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Nonlinear MPC Versus MPC Using on-Line Linearisation — A Comparative Study

Cited by 8 publications

References 8 publications

Latent variable based model predictive control: Ensuring validity of predictions

Latent variable based model predictive control: Ensuring validity of predictions

Nonlinear parametric predictive control. Application to a continuous stirred tank reactor

LTI-MPC for the Micro-grid Control

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