Active Suspension Control Using an MPC-LQR-LPV Controller with Attraction Sets and Quadratic Stability Conditions

The control of an automotive suspension system by means of a hydraulic actuator is a complex nonlinear control problem. In this work, a linear parameter varying (LPV) model is proposed to reduce the complexity of the system while preserving the nonlinear behavior. In terms of control, a dual control...

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Veröffentlicht in:	Mathematics (Basel) 2021-10, Vol.9 (20), p.2533
Hauptverfasser:	Rodriguez-Guevara, Daniel, Favela-Contreras, Antonio, Beltran-Carbajal, Francisco, Sotelo, David, Sotelo, Carlos
Format:	Artikel
Sprache:	eng
Schlagworte:	Active control active suspension Actuators Algorithms attraction sets Complexity Control algorithms Control stability Controllers Design specifications ellipsoidal set Fuzzy logic Hydraulic equipment Hydraulics Linear matrix inequalities linear parameter varying Linear quadratic regulator Mathematics model predictive control Nonlinear control Predictive control quadratic stability Scheduling Suspension systems
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Zusammenfassung:	The control of an automotive suspension system by means of a hydraulic actuator is a complex nonlinear control problem. In this work, a linear parameter varying (LPV) model is proposed to reduce the complexity of the system while preserving the nonlinear behavior. In terms of control, a dual controller consisting of a model predictive control (MPC) and a Linear Quadratic Regulator (LQR) is implemented. To ensure stability, quadratic stability conditions are imposed in terms of Linear Matrix Inequalities (LMI). Simulation results for quarter-car model over several disturbances are tested in both frequency and time domain to show the effectiveness of the proposed algorithm.
ISSN:	2227-7390 2227-7390
DOI:	10.3390/math9202533