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Start Over Descriptor "ellipsoidal set" Publisher mdpi ag
2 results on '"ellipsoidal set"'

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

Author

Daniel Rodriguez-Guevara, Antonio Favela-Contreras, Francisco Beltran-Carbajal, David Sotelo, and Carlos Sotelo

Subjects
active suspension, model predictive control, linear parameter varying, ellipsoidal set, attraction sets, quadratic stability, Mathematics, QA1-939
Abstract

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.

Published
2021
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2. Active Suspension Control Using an MPC-LQR-LPV Controller with Attraction Sets and Quadratic Stability Conditions

Author

Carlos Sotelo, Daniel Rodriguez-Guevara, David Sotelo, Francisco Beltran-Carbajal, and Antonio Favela-Contreras

Subjects
active suspension, model predictive control, General Mathematics, ellipsoidal set, Linear-quadratic regulator, Nonlinear control, Active suspension, Hydraulic cylinder, Nonlinear system, Model predictive control, quadratic stability, linear parameter varying, Control theory, Computer Science::Systems and Control, Computer Science (miscellaneous), QA1-939, Time domain, attraction sets, Engineering (miscellaneous), Mathematics
Abstract

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.

Published
2021

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