Experimental Methods Of Intelligent Control For Autonomous Mobile Robot

The study of the intelligent control method is an important research direction in the field of robot control. The control ways based on neural network has strong robustness and adaptability, which opens up a new way to solve the complicated nonlinear robot, and uncertain, unknown system control problem. Combining with laboratory robot control system teaching equipment, this thesis studies the reasons in planar motion of the robot error and elated control method, realizes the conventional PID control algorithm to control the linear motion of the mobile robot through the program. Aiming at the shortcomings of the conventional PID controller, it combines with the neural network and the conventional PID control algorithm to design a new PID control based on BP neural network. Through the neural network to real-time PID parameters setting, it realizes the wheel speed around the robot closed loop control solution, accomplishes in the mobile robot, and gets a better control effect. The research will lead to better implement robot control teaching work. The paper is mainly concerned with the following:(1) The servo and mechanism of autonomous mobile robot (AS-UII Intelligent Robot) are introduced; designs some general programme to make the mobile robot implement the elementary movement; measured the actual differentiate rate and the drive characteristic by programming; implement the traditional PID control algorithm and get the three parameters of the traditional PID controller.(2) It includes analysis of the advantages and disadvantages of conventional PID control, the application of neural network control system. It describes in detail PID control with the combination of neural network theory setting as the neural network PID controller theoretical basis. It also introduces the designation and Matlab simulation of the neural network design PID controller. Comparing with the traditional,open-loop control, neural network can be very good for PID Self-tuning parameters.(3) It realizes the PID control algorithm based on BP network using VJC to programme and download to the autonomous mobile robot to get the independent linear motion. From the actual effects, the conclusion based on the BP neural network PID controller have strong real-time online adjust the control parameters of ability, greatly reducing the traditional experiment method using the workload, obviously improve the control accuracy, increase the stability of the system.