This paper presents a model predictive control approach to drive the vehicle up to its tires adhesion limits. The main focus is optimality of the closed-loop control to follow a certain track in minimum time. A Linear Time Varying Model Predictive Controller (LTV-MPC) is developed to be able to adapt with high non-linearities of the model, but also having low computational complexity in order to work in real-time. In order to have the best reference trajectory and apply it to the LTV-MPC, the problem is first solved in a nonlinear optimal control framework. This solution represents a benchmark as well, to which the LTV-MPC results are compared. The proposed controller is tested in simulation showing promising results.
A Model Predictive Controller for Minimum Time Cornering
MALMIR, MOHAMMADHOSSEIN;Marco Baur;Luca Bascetta
2018-01-01
Abstract
This paper presents a model predictive control approach to drive the vehicle up to its tires adhesion limits. The main focus is optimality of the closed-loop control to follow a certain track in minimum time. A Linear Time Varying Model Predictive Controller (LTV-MPC) is developed to be able to adapt with high non-linearities of the model, but also having low computational complexity in order to work in real-time. In order to have the best reference trajectory and apply it to the LTV-MPC, the problem is first solved in a nonlinear optimal control framework. This solution represents a benchmark as well, to which the LTV-MPC results are compared. The proposed controller is tested in simulation showing promising results.File | Dimensione | Formato | |
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