A Modified Block Backstepping Controller for Autonomous Vehicle Lane Changing

Abstract

In this paper, a modified block backstepping controller was formulated for double lane changing control of a two-degree-of-freedom (2DOF) autonomous vehicle. For a systematic procedure, a 5th-degree polynomial double lane change trajectory was created. Next, the state model dynamics of this underactuated 2DOF autonomous vehicle is presented, which was transformed into the block-strict feedback form. Thereafter, the block backstepping technique was implemented to achieve the control input (steering angle). For enhancing the steady state performance during the trajectory tracking, an integral action was included in the proposed controller. The stability of this controller was established through the Lyapunov theory. To investigate the effectiveness of this proposed controller, we compared it with a human driver's transfer function controller and LQR controller, in addition to the sliding mode controller. Simulation results were achieved using CarSim-Simulink. Later, this controller was implemented to track the same lane change path with a different road coefficient of friction. The supposed controller characteristic was further investigated by inspecting the motion of the vehicle when exposed to an idealized lateral step force disturbance. The simulation results indicated the power of modified block backstepping control and it has higher following accuracy, better yaw rate tracking, and stable front steering angle, at high speed and at high and low friction roads.

Unsupervised Machine Learning Control Techniques for Solving the General Synthesis of Control System Problem

“…The control synthesis problem is currently being solved using many analytical techniques, such as integrator backstepping [11,12], analytical design of aggregated regulators (ADAR) [13,14], and control Lyapunov functions [15,16].…”