Abstract
The tracking system of robot was optimized by using the fuzzy BP neural network PID control algorithm in this paper, which was based on the traditional PID control algorithm. The control algorithm combines the functions of fuzzy control, the neural network control and the traditional PID control algorithm, which resulted The PID control has the ability of logical reasoning and computing. The system collects the scheduled route information through the sensor module and altogether with the actual output of the system constitute the excitation signal of the neural network. The MATLAB software is used to simulate the system in this paper, compared with the result of the simulation of traditional PID control algorithm. The result shows that optimize design of wheeled robot tracking system with PIDcontrol algorithm based on BP neural network has better adaptive ability and self-learning ability and the improvement of the stability of wheeled robot tracking system.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Similar Papers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.