Coordinated Control of Dual-Motor Using the Interval Type-2 Fuzzy Logic in Autonomous Steering System of AGV

Abstract

To achieve better trajectory tracking of the autonomous ground vehicle (AGV), a dual-motor autonomous steering structure and control method are proposed. The model predictive control (MPC) algorithm is utilized to calculate the optimal front wheel angle in real time based on the vehicle information, and dual-motor steering system follows the target angle to achieve trajectory tracking. In this process, to improve the stability of the angle motor, a coordinated steering controller of the angle motor and torque motor is proposed, and the type-2 fuzzy logic is designed based on the target front wheel angle and vehicle speed to optimize coordination coefficient. The front wheel angle step input and double-lane change trajectory tracking conditions are simulated in the carsim and simulink joint simulation platform, the results show that dual-motor steering system has good trajectory tracking ability, compared with no coordinated control, the current and velocity of angle motor are more stable under the coordinated steering control, which greatly reduces the steering load of the angle motor under different working conditions. The final hardware-in-loop test is put forward to verify the effectiveness of the MPC controller and coordinated steering controller.