Hybrid Parameter-varying Model Predictive Control for Autonomous Vehicle Steering

In this paper the concept of Hybrid Parameter-Varying Model Predictive Control (HPV-MPC) is applied for autonomous vehicle steering. Parameter-varying in the MPC context means that a prediction model with non-constant, parameter-varying system matrices is employed. In the investigated scenarios, the...

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Bibliographic Details
Published in:European journal of control 2008, Vol.14 (5), p.418-431
Main Authors: Besselmann, Thomas, Morari, Manfred
Format: Article
Language:English
Subjects:
Algorithms
automotive
model predictive control
Predictive control
Studies
Vehicle steering
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Summary:In this paper the concept of Hybrid Parameter-Varying Model Predictive Control (HPV-MPC) is applied for autonomous vehicle steering. Parameter-varying in the MPC context means that a prediction model with non-constant, parameter-varying system matrices is employed. In the investigated scenarios, the displacement of a car on an icy road due to a side wind gust shall be mitigated, and a double lane-change maneuver shall be performed autonomously. In order to explore a possible reduction of online computations and the inherent degradation of control performance, the nonlinear model of the lateral dynamics is approximated in various ways. A comparison between controllers using prediction models varying from the full nonlinear model, as an indication for the maximal achievable performance, to a linear model was performed. Particular emphasis was put on the hybrid parameter-varying prediction model, to investigate their potential in terms of computational effort and control performance.
ISSN:0947-3580
1435-5671
DOI:10.3166/ejc.14.418-431