A model-based nonlinear wheel slip controller for ABS (Anti-lock Brake Systems) is designed using LQ-(Linear Quadratic-)optimal control. The controller gain matrices are gain scheduled on the vehicle speed. A parameter dependent Lyapunov function for the nominal LPV (Linear Parameter Varying) closed loop system is found by solving a LMI (Linear Matrix Inequality) problem. This Lyapunov function is used to investigate robustness with respect to uncertainty in the road/tyre friction characteristic. In order to achieve robustness, the approach does not rely on explicit knowledge of the tyre/road friction curve. Static uncertainty is eliminated using integral action, while dynamic uncertainty is handled by a robust design with a sufficient stability margin. Experimental results from a test vehicle with electromechanical brake actuators and brake-by-wire show that high performance and robustness are achieved. Although a detailed comparison with commercially available off-the-shelf ABS has not been conducted, the present results are encouraging, in particular when taking into account the modest time taken to design, tune and commission this model-based approach. The robustness analysis and redesign based on the experimental experience shows that there are possibilities for further improvement of the control algorithms and tuning.
Wheel slip control using gain-scheduled LQ - LPV/LMI analysis and experimental results
Adaptive, linear-quadratische Radschlupfregelung anhand LMI-(Lineare Matrix-Ungleichheit-)Analyse eines parameterabhängigen, linearen, dynamischen Systems und experimentelle Ergebnisse
2003
6 Seiten, 7 Bilder, 27 Quellen
Conference paper
Storage medium
English
Wheel slip control in ABS breaks using gain scheduled constrained LQR
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