Adaptive velocity control of an autonomous vehicle using input-error model reference approach

Abstract

The input error model reference adaptive control (IE-MRAC) is employed to regulate the longitudinal velocity of an autonomous vehicle to desired values by controlling both the throttle and the braking system. The proposed method deals with matching the unknown longitudinal model of the vehicle with a predefined model in the presence of various disturbances, including road conditions and aerodynamic effects. Moreover, it is shown that the saturation on the throttle and the brake pedals are successfully handled due to the properties of the derived error equation. Besides analyzing the natural properties of IE-MRAC, a novel stability proof of the closed-loop system is presented, and a robust modification of the adaptive control law is given as well. By using the proposed control technique, higher-order tracking is captured, and the effects on enhancing the vehicle responses are investigated. The applicability of the presented theoretical results is validated via the CarSim simulator.