ABSs系统模糊控制器优化设计

Design of An Optimal Fuzzy Controller for Antilock Braking Systems

已经开发了的ABSs系统改善了突然制动和特别是滑动路面状况时车辆控制。这样的控制目标是在保持车辆合适稳定性及可操纵性和缩短车辆刹车距离情况下在要求的方向增大车轮的牵引力。本文提出了ABSs系统优化的模糊控制器。从保持其车轮滑动值为目标函数获得车轮最大的牵引力和车轮最大的减速度。采用遗传算法优化模糊系统的全部组件。采用误差数整体优化方法收敛接近最优点。仿真结果表明快速收敛和对不同路况的控制器的最好性能。

Antilock braking systems（ABSs） have been developed to improve Vehicle control during sudden braking, especially on slippery road surfaces. The objective of such control is to increase wheel traction force in the desired direction while maintaining adequate vehicle stability and steerability and reducing the vehicle stopping distance. In this paper, an optimized fuzzy controller is proposed for ABSs. The objective function is defined to maintain the wheel slip to a desired level so that maximum wheel traction force and maximum vehicle deceleration are obtained. All the components of a fuzzy system are optimized using genetic algorithms. The error-based global optimization approach is used for fast convergence near the optimum point. Simulation results show fast convergence and good performance of the controller for different road conditions.