Independent Vehicle Tracking Control System

With the development of science and technology, embedded system has been more and more widely used in the field of control, and the development of intelligent vehicle based on embedded in intelligent transportation system (ITS) plays a more and more important role. In this paper, the research takes the smart car of the four-wheel independent drive as the key object, and adopts Cortex-M3 as the main controller, designed intelligent vehicle motion control system, including environment apperception, decision-making.Smart car control system and each module are analyzed in detail in the paper first, and then the kinematic model was established according to movement characteristic for provides theory basis for the design of the control system. In tracking algorithm design, with car body off center deviation and deviation rate as input to design the fuzzy controller, the design of speed value of the photoelectric sensor feedback PID control algorithm for closed loop control, and carries on the simulation using the matlab tool, verify the fuzzy control algorithm and the effectiveness of the fuzzy adaptive PID control algorithm, finally, on the architecture M3 transplant embedded real-time operating system uC/OS-Ⅱ, multitasking programming function module of the smart car management, improve the real-time performance of the control system of smart car.This paper mainly completed the following work:first, according to the selection of main controller and sensor, design of embedded system hardware control circuit. Second, to set up the kinematics model of the smart car, respectively adopt fuzzy control algorithm and fuzzy adaptive PID control algorithm for smart car steering gear and drive motor to control, and carries on the simulation using the matlab tool, verify the validity of the control algorithm. Third, through the transplant embedded real-time operating system uC/OS-II to the main controller architecture M3, multitasking programming for smart car to implement multitasking management, according to the target position to control the steering direction and speed to achieve the best effect of tracking.