基于BP神經(jīng)網(wǎng)絡PID算法的多電機同步控制研究
發(fā)布時間：2019-05-15 15:50
【摘要】：近年來隨著工業(yè)自動化程度的不斷提高,傳動系統(tǒng)也提出了更加嚴苛的要求。傳動控制系統(tǒng)在工農(nóng)業(yè)生產(chǎn)中得到越來越廣泛的應用,多電機控制的研究顯得尤為重要。多電機同步控制精度的提高將直接帶動工農(nóng)業(yè)生產(chǎn)效率提升,帶來極大的經(jīng)濟效應,因而多電機同步控制的研究越來越受到人們的關注。本文主要從多電機控制策略和多電機同步控制方式兩個方面進行研究。首先,在多電機同步控制系統(tǒng)中需要單臺電機具有很好的速度跟隨特性,因而單臺電機控制效果的好壞將直接制約著多電機同步控制系統(tǒng)的精度。工農(nóng)業(yè)生產(chǎn)中主要是以傳統(tǒng)PID控制器來提升控制器響應速率。傳統(tǒng)PID控制器簡單易實現(xiàn),但是PID參數(shù)整定比較困難,對于多電機同步控制系統(tǒng)這樣一個多變量、非線性、強耦合的控制對象而言顯得捉襟見肘。因而,本文采用BP神經(jīng)網(wǎng)絡PID替代傳統(tǒng)PID控制器,在深入研究過程中發(fā)現(xiàn)傳統(tǒng)BP神經(jīng)網(wǎng)絡算法具有收斂速度慢、易陷入局部極小值等缺陷,提出引入慣性項、引入動量項、改進搜索方向、改進學習速率四點改進策略,重新設計基于改進BP神經(jīng)網(wǎng)絡的PID控制器,改善BP神經(jīng)網(wǎng)絡PID控制器性能。其次,在多電機同步控制系統(tǒng)中,多電機同步控制方式與多電機的同步控制精度也是關系密切。本文將并行控制、主從控制、交叉耦合控制和偏差耦合控制進行比較研究,得出偏差耦合控制能夠較好的解決多電機同步控制問題,但是傳統(tǒng)偏差耦合控制速度補償器對于各臺電機之間的同步誤差修正不夠快,反應不夠靈敏。因而本文提出了三點改進速度補償器的策略:引入速度信號補償增益、引入誤差因子、添加BP神經(jīng)網(wǎng)絡PID控制器。重新設計了偏差耦合控制速度補償器,改善速度補償器的不足。最后,在Matlab/Simulink環(huán)境下搭建多電機同步控制系統(tǒng)的仿真控制平臺,進行仿真實驗分析,從實驗結果可以看出本文所做研究明顯提高了多電機同步控制精度。
[Abstract]:In recent years, with the continuous improvement of the degree of industrial automation, the transmission system has made more demanding requirements. The transmission control system is more and more widely used in industrial and agricultural production, and the research of multi-motor control is particularly important. The improvement of multi-motor synchronous control precision will directly drive the efficiency of industrial and agricultural production and bring great economic effect, so the research of multi-motor synchronous control is more and more concerned. In this paper, the two aspects of multi-motor control strategy and multi-motor synchronous control are studied. First, in the multi-motor synchronous control system, a single motor is required to have a good speed-following characteristic, so that the control effect of a single motor will directly restrict the accuracy of the multi-motor synchronous control system. In the industrial and agricultural production, the response rate of the controller is improved by using the traditional PID controller. The traditional PID controller is simple and easy to implement, but the PID parameter setting is difficult. For a multi-variable, non-linear, strong-coupled control object of the multi-motor synchronous control system, it is difficult to see. In this paper, the BP neural network PID is used to replace the traditional PID controller. In the course of the in-depth study, it is found that the traditional BP neural network algorithm has the defects of slow convergence speed, easy to fall into local minimum, etc. The inertia term is introduced, the momentum term is introduced, and the search direction is improved. Improve that four-point improvement strategy of the learning rate, and re-design the PID controller based on the improved BP neural network to improve the performance of the BP neural network PID controller. Secondly, in the multi-motor synchronous control system, the synchronous control accuracy of the multi-motor synchronous control system and the multi-motor is also closely related. In this paper, the parallel control, the master-slave control, the cross-coupling control and the bias coupling control are compared and studied, and the problem of synchronous control of the multi-motor can be solved well by the deviation coupling control. But the conventional deviation coupling control speed compensator is not fast enough to correct the synchronous error between the motors, and the reaction is not sensitive enough. The strategy of three-point improved speed compensator is proposed in this paper. The speed signal compensation gain is introduced, the error factor is introduced, and the BP neural network PID controller is added. The deviation coupling control speed compensator is redesigned to improve the speed compensator. Finally, the simulation control platform of the multi-motor synchronous control system is set up in the environment of Matlab/ Simulink, and the simulation experiment is carried out.
【學位授予單位】：沈陽工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM301.2
[Abstract]:In recent years, with the continuous improvement of the degree of industrial automation, the transmission system has made more demanding requirements. The transmission control system is more and more widely used in industrial and agricultural production, and the research of multi-motor control is particularly important. The improvement of multi-motor synchronous control precision will directly drive the efficiency of industrial and agricultural production and bring great economic effect, so the research of multi-motor synchronous control is more and more concerned. In this paper, the two aspects of multi-motor control strategy and multi-motor synchronous control are studied. First, in the multi-motor synchronous control system, a single motor is required to have a good speed-following characteristic, so that the control effect of a single motor will directly restrict the accuracy of the multi-motor synchronous control system. In the industrial and agricultural production, the response rate of the controller is improved by using the traditional PID controller. The traditional PID controller is simple and easy to implement, but the PID parameter setting is difficult. For a multi-variable, non-linear, strong-coupled control object of the multi-motor synchronous control system, it is difficult to see. In this paper, the BP neural network PID is used to replace the traditional PID controller. In the course of the in-depth study, it is found that the traditional BP neural network algorithm has the defects of slow convergence speed, easy to fall into local minimum, etc. The inertia term is introduced, the momentum term is introduced, and the search direction is improved. Improve that four-point improvement strategy of the learning rate, and re-design the PID controller based on the improved BP neural network to improve the performance of the BP neural network PID controller. Secondly, in the multi-motor synchronous control system, the synchronous control accuracy of the multi-motor synchronous control system and the multi-motor is also closely related. In this paper, the parallel control, the master-slave control, the cross-coupling control and the bias coupling control are compared and studied, and the problem of synchronous control of the multi-motor can be solved well by the deviation coupling control. But the conventional deviation coupling control speed compensator is not fast enough to correct the synchronous error between the motors, and the reaction is not sensitive enough. The strategy of three-point improved speed compensator is proposed in this paper. The speed signal compensation gain is introduced, the error factor is introduced, and the BP neural network PID controller is added. The deviation coupling control speed compensator is redesigned to improve the speed compensator. Finally, the simulation control platform of the multi-motor synchronous control system is set up in the environment of Matlab/ Simulink, and the simulation experiment is carried out.
【學位授予單位】：沈陽工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM301.2
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