| With the rapid development of modern industry,single motor control system is more and more difficult to meet the control requirements of automatic control system.The multi-motor synchronous control system has significant advantages in improving the output torque and execution ability of the control system,reducing the demand of the high-torque actuator on motors,reducing the complexity of intermediate transmission mechanism and so on.Therefore,the multi-motor synchronous control system has been widely used and the synchronous control of machine equipment has become a hot research content in the field of motion control.The accuracy and stability of multi-motor synchronous control system will be reduced due to the effect of friction,electromagnetic interference,load changes,motor parameters changes and other adverse factors,thus the product quality,system safety and other factors are adversely affected.Therefore,it is of great significance for the development of theoretical research and engineering application to launch research on the control methods of multi-motor synchronous control system and improve the control accuracy and stability.Permanent magnet synchronous motor speed synchronous control system was taken as the research object,control accuracy and stability improving of multi-motor synchronous control system were taken as research purposes.The research was launched from tracking accuracy optimization,synchronization accuracy optimization and stability optimization.Aiming at the problem of poor speed tracking accuracy,a fuzzy PID tracking control algorithm based on optimized subsets was proposed to optimize the performance of fuzzy PID control and improve the tracking accuracy.Aiming at the problem of poor synchronization accuracy,a relative coupling algorithm based on optimized synchronization error compensation method was proposed to ameliorate the synchronization error control ability and improve the synchronization accuracy.Aiming at the problem of poor stability,a relative coupling anti-interference algorithm based on elite iterative learning was proposed.The elite iterative strategy was proposed to compensate the periodic disturbances and improve stability of the control system.The main work of this thesis are as follows:(1)The principle and characteristics of permanent magnet synchronous motor were introduced.Permanent magnet synchronous motor was taken as modeling object,based on the transfer function control method,the single motor control model and multi-motor synchronous control model were established respectively.The construction method of transfer function and parameters setting method were introduced.The theoretical basis and simulation control models were provided for the subsequent research work.(2)Aiming the problem of poor speed tracking accuracy,a fuzzy PID tracking control algorithm based on optimized subsets was proposed.The cross arrangement was adopted for setting subsets,and the Adaptive Genetic Algorithm Based on Improved Crossover and Mutation Operator was used to offline optimize the fuzzy subset parameters of the input membership function by taking the global tracking error as fitness function.The fuzzy subsets corresponding to the minimum global tracking error were searched.By constructing motor speed tracking control simulation experiment,compared with PID control,traditional fuzzy PID control and variable universe fuzzy PID control algorithms,the result showed that compared with the PID control algorithm,the overshoot value,stability time and global self-tracking error indexes are improved by 88.91%,23.16% and 25.90%;compared with the traditional fuzzy PID control algorithm,the indexes are improved by 84.78%,12.75% and 12.42%,respectively;compared with the variable universe fuzzy PID control algorithm,the indexes are improved by 81.79%,12.70%,16.78%,respectively.The speed tracking accuracy of multi-motor synchronous control system is improved by the mothed and the system work quality and safe operation ability is improved.(3)Aiming at the problem of poor synchronization accuracy,a relative coupling algorithm based on optimized synchronization error compensation method was proposed.Based on the traditional relative coupling algorithm,a gain equation was added.The gain coefficients in the equation were dynamically adjusted by comparing the absolute value of the tracking errors in real time to realize the dynamic adjustment of the synchronous error compensation speed.The Adaptive Genetic Algorithm Based on Improved Crossover and Mutation Operator was applied to offline optimize the gain coefficients to search the gain coefficients corresponding to the minimum global synchronization error.By constructing 4 motors synchronization control simulation experiment,compared with traditional relative coupling algorithm and improved relative coupling algorithm,the experimental results showed that compared with the traditional relative coupling algorithm,the overshoot value indexes of 4 motors are improved by 46.41%,20.58%,44.92% and 15.82%,respectively;compared with the improved relative coupling algorithm,the indexes are improved by 51.21%,30.42%,49.86% and 23.36%,respectively;The static difference and stability time of the three algorithms are equal for same motor.The synchronization accuracy of multi-motor synchronous control system is improved by the mothed and the ability of the system to perform complex tasks is improved.(4)Aiming at the problem of poor stability,a relative coupling anti-interference algorithm based on elite iterative learning was proposed.The traditional deviation coupling algorithm was combined with the elite iterative learning strategy to compensate the periodic interference signals,so as to improve the stability.The Adaptive Genetic Algorithm Based on Improved Crossover and Mutation Operator was used to offline optimize the learning gain coefficients corresponding to the optimal stability.By constructing 4 motors synchronization control simulation experiment,compared with traditional relative coupling algorithm,relative coupling algorithm applying traditional iterative learning and relative coupling algorithm applying iterative learning with forgetting factor,the result showed that the convergence of tracking error and synchronization error are achieved steadily by proposed method;compared with the traditional relative coupling algorithm,the global tracking error and global synchronization error indexes are increased by 81.54% and 88.85%,respectively;compared with the relative coupling algorithm applying iterative learning with forgetting factor,the indexes are increased by 28.67% and 41.80%,respectively.The stability of multi-motor synchronous control system is improved by the method and the ability of the system to work in the interference environment is improved. |
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