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The aim is to design a nonlinear model predictive control (MPC) law that stabilizes systems with nonlinearities.

Nonlinear MPC Design using the qLPV Approach and IQC-based Terminal Ingredients

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The aim is to design a nonlinear model predictive control (MPC) law that stabilizes systems with nonlinearities.
Develop a nonlinear MPC design procedure using IQC-based terminal ingredients.
Utilize quasi-linear parameter varying (qLPV) models to lessen computational demand.
Perform simulations and a real processor-in-the-loop validation experiment.
The proposed scheme demonstrates improved control performance compared to existing nonlinear MPC algorithms.
Larger regions of attraction are achieved through the use of IQC-based terminal ingredients.
Lower numerical costs are noted during the control process.

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Our approach combines nonlinear MPC with IQC-based elements to enhance stability and reduce computational load in nonlinear systems.

Morato et al. (2026) studied this question.

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