Self-Tuning Speed Tracking Controller for a Portable Brake and Throttle Robot

摘要

Vehicle testing often requires accurate speed control, whether maintaining a constant speed or following a dynamic speed profile. A portable brake and throttle robot designed for this task must quickly and automatically adapt its control to each test vehicle's mass and powertrain characteristics in order for the controller to perform well on a wide variety of platforms. This application presents two major challenges. First, each new vehicle installation requires rapid retuning of the controller. Manual tuning can be very time-consuming. Second, the "plant" is very nonlinear and asymmetric. Different actuators are employed for acceleration (engine) and braking (road loads and friction brakes). After a broad survey of control strategies and their suitability for this particular application, neurofuzzy techniques were among the most promising. Neurofuzzy networks can not only approximate nonlinear functions accurately, but the fuzzy rule-consequent weights can be readily updated in real time. A neurofuzzy controller was designed for the automotive speed tracking problem. Experimental testing was conducted and results were presented and analyzed.