An Intelligent Control Algorithm Applied to The Flow Control of Phosphor Colloid

During the LED coating process, the flow of the phosphor colloid at the spray gun has a great impact on the correlated color temperature. It is difficult for the PID control method to use the flow characteristics of non-Newtonian fluids of the fluorescent colloid to achieve the accurate and stable control of the flow, and it has been adjusted by expert knowledge and trial and error methods. To improve the luminous performance, an RBF neural network (RBFNN) of fractional-order PID control algorithm based on sparrow search algorithm (SSA) is proposed in this paper, referred to as SSA-RBFNN-FOPID. Firstly, the parameters of the RBF neural network are optimized to improve the training speed and accuracy by using the sparrow search algorithm. Secondly, the optimal parameters of fractional-order PID are tuned online by using the optimized RBF neural network. In the end, experimental results show that the proposed algorithm has excellent dynamic and static performance, stronger robustness and anti-interference ability compared with other advanced algorithms, which is conducive to more accurate and stable control of the flow of fluorescent colloid during the coating.