Fuzzy Model Reference Adaptive Controller for Position Control of a DC Linear Actuator Motor in a Robotic Vehicle Driver

Abstract

This paper presents the controller development for DC linear actuator motors that are used to control the throttle and brake pedals of a passenger car with automatic transmission. The Fuzzy Model Reference Adaptive Control (Fuzzy MRAC) system allows the vehicle to follow speed vs. time profiles of driving cycles by dynamically adjusting the position of the driver pedals in a vehicle. The designed controller is implemented to a virtual vehicle model to determine the required position of the linear pedal actuators over a standard driving cycle. The driving-cycle simulation is conducted using Matlab Simulink and the performance of the controller is analyzed based on overshoot, rise time, settling time and mean square error whereas the robustness test was carried out via set-point tracking method. The result shows 19.7988 s rise time, 0.1619% overshoot, 32.6532 s settling time and 0.0041 mean square error. The results have proven Fuzzy MRAC to be a viable option for use in highly dynamic systems such as automotive standard driving cycle controllers.