Adaptive Control of Autonomous Vehicles

Abstract

Autonomous vehicles belong to a class of systems whose dynamic characteristics are independent of time. Due to their nonlinear dynamics, classical theories that deal with linear systems are no longer applicable in the analysis or design. The specific autonomous vehicle considered in this work was an underactuated quadrotor with more degrees of freedom than the number of actuations. At the same time, the quadrotor was assumed to have an unknown mass and experience constant force disturbances. A model-reference adaptive control strategy was designed with an observer and controller to implement desired trajectory tracking behavior of the quadrotor. The overall stability of the motion was guaranteed with a Kalman-Bucy filter for the design of the state observer and Lyapunov-based backstepping techniques for the design of the adaptive state feedback controller.