Research Of Multi-motor Cooperative Control Method Based On Intelligent Optimization Algorithm

With the continuous development of industrial automation technology,people have higher and higher requirements for the operation stability and control accuracy of multi motor cooperative control systems,such as welding,CNC machine tools,robot control systems and so on.Due to the problems of simple control structure,low precision and poor real-time performance,the traditional single motor control method can not be directly transplanted to multi motor system.Therefore,the research on the cooperative control method of multi motor system has become an urgent need for its wide application.This paper studies the cooperative control of multi brushless DC motor,designs an improved ring coupling control structure,and studies the intelligent PID(proportional,integral,differential)control algorithm based on this structure to realize the high-precision cooperative control of multi motor system.The specific research contents are as follows:(1)The structure and working mechanism of brushless DC motor are analyzed,and its mathematical model and spatial state model are determined.This paper analyzes the principle of multi motor cooperative control,summarizes the advantages of each multi motor cooperative control structure,and then designs an improved ring coupling structure of multi motor cooperative control.The structure uses the average of the speed of two adjacent motors and the real-time speed of multiple motors,and adds a dynamic factor to the speed compensator to enhance the real-time performance and control accuracy of the ring coupling control structure.(2)Based on the designed ring coupling control structure,a PID control algorithm based on fuzzy optimization is proposed to realize multi motor control.The algorithm takes the motor speed deviation E and the motor speed deviation change rate EC as the inputs of the fuzzy PID controller,and obtains the optimized PID controller proportion coefficient KP0,integral coefficient KI0 and differential coefficient KD0 through fuzzy reasoning,so as to optimize the motor controller.Since the input speed deviation of the algorithm comes from the improved speed compensator,the input variable domain is dynamically adjusted according to the speed error range.At the same time,the proportional distribution of triangular membership function is adopted to improve the robustness of the controller.Fuzzy rules are generated by fuzzy sets,and a fuzzy rule base with three coefficients is established.The Mamdani reasoning method is used for fuzzy reasoning,and the center of gravity method is used to solve the fuzzy operation to obtain the optimized PID controller parameters,so as to ensure the coordination and reliability of the multi motor system,and optimize the steady-state performance and accuracy of the system under different load conditions.In the improved ring coupling structure,the performance of multiple motors is tested to verify the performance of the algorithm.(3)Due to the poor self-tuning of the proportional coefficient,differential coefficient and integral coefficient of the fuzzy controller,a hybrid particle swarm optimization algorithm is proposed to optimize the fuzzy rules of the fuzzy PID algorithm,realize the automatic optimization and tuning of the controller parameters,and then improve the coordination of the multi motor control system.In order to improve the convergence accuracy of the algorithm,combined with particle swarm optimization algorithm,we can get the global optimal solution and the individual historical optimal solution.After that,the operation can be carried out in combination with the natural selection algorithm,and the fitness function can be introduced to reorder the particles.After that,the particles with low fitness can be deleted directly,and all of them are the historical optimal value.It increases the diversity of the algorithm population and helps the algorithm escape from the local optimal solution faster.Finally,simulation modeling is carried out,and the control performance of multi motor system before and after algorithm optimization is compared and analyzed to verify the superiority of fuzzy PID control algorithm based on hybrid particle swarm optimization.This paper designs an improved ring coupling control structure,designs a multi motor cooperative control system based on the improved structure,and puts forward the corresponding intelligent optimization algorithm to optimize the controller of the motor system.The simulation results show that the proposed algorithm can effectively improve the stability,reliability and cooperation ability of multi motor control system,provide a reference for the application of intelligent control algorithm in multi motor cooperative control system,and promote the wide application of intelligent optimization algorithm in the field of multi motor cooperative control.