Abstract
In the process of LED chip coating, the steady flow at the spray gun in a unit time has a significant impact on the final luminous effect. Traditional PID control is difficult to control the flow accurately due to the nonlinearity of phosphor powder. In order to improve the luminous quality, a neural network PID control method based on wolf pack algorithm is proposed(WPA-BPNN-PID) in this paper. First, the weights and thresholds of BP neural network are optimized by using the wolf pack algorithm to improve the training speed and prediction accuracy. Second, the optimal PID control parameters are searched online by using the optimized BP neural network. Finally, the traditional PID control algorithm, neural network PID control algorithm and WPA-BPNN-PID algorithm are simulated by MATLAB simulation software. The experimental results show that the proposed WPA-BPNN-PID algorithm has better dynamic and static performance, anti-interference ability, and thus can further accurately control the colloid flow of phosphor powder in unit time.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
