防抱制动系统模糊模型参考学习控制的研究

Fuzzy Model Reference Learning Control for Anti-lock Braking System

在保持可操纵性的前提下,提高车辆制动效能是设计防抱制动系统的主要目的。为此,设计了防抱制动系统的模糊模型参考学习控制器。由于该控制器引入了模糊学习机制,通过观察被控对象和代表理想动态性能的参考模型的输出差,从而调整模糊控制器的规则集,以使对象输出跟踪参考模型的输出。而后建立了直线制动车辆系统的数学模型,基于MATLAB/SIMULINK工具箱,并对所设计的模糊模型参考学习控制系统在不同的路面状态下进行了模拟,仿真结果表明,该控制方案是合理可行的。

Anti-lock braking system (ABS) is designed to improve vehicle-braking effectiveness while maintaining steerability. To this end, the fuzzy model reference learning control (FMRLC) is presented. The controller utilizes a learning mechanism that observes the behavior of the fuzzy control system, compares the system performance with a model of the desired system behavior, and modifies the fuzzy controller to more closely match the desired system behavior. Vehicle mathematical model for straight line braking is built. Then, based on MATLAB/SIMULINK toolbox, the performance of the FMRLC-based ABS is simulated for various road conditions. Simulation results show that the control scheme proposed is feasible.