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Study on Neural Network Self-Tuning PID Control Method for Electro-Hydraulic Servo System

Author: WeiYaJuan
Tutor: JiangWanLu
School: Yanshan University
Course: Mechanical and Electronic Engineering
Keywords: Electro-hydraulic position servo system Neural Network PID Virtual instrument Matlab simulation Parameters on-line adjustment
CLC: TP271.31
Type: Master's thesis
Year: 2009
Downloads: 274
Quote: 3
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Abstract


With the development of automation technology and the continuous improvement of the degree of automation of industrial systems , electro-hydraulic servo system stability , fast , accuracy and adaptability control quality put forward higher requirements. To meet these requirements , on the one hand, to increase the level of manufacturing process and quality characteristics of the hydraulic components ; controller designed performance on the other hand become a key technology . PID control is widely used as a practical engineering system control method , but changes in the model parameters , and the system has a strong nonlinearity and time delay factors exist parameter tuning difficulties , control quality and system robustness owe good shortcomings . In this paper, the control characteristics of the electro-hydraulic servo system , the neural network self- tuning PID control strategy research , neural network tuning PID controller parameters online to improve the quality of the controlled system 's dynamic . First of all, the neural network theory of self- tuning PID controller . The controller is made ??up of classic PID controller and neural networks , closed-loop control of the classic PID controller directly controlled object ; neural network based on the operational status of the system , through the online self-learning to adjust the weighting coefficients , real-time adjustment of PID control With the parameters K_p K_i , K_d PID controller parameters of the neural network output optimal sense . Secondly , the establishment of the mathematical model of the material the test Hydromechatronics position servo system , the choice of the relevant parameters of the system , a simulation model using Simulink package , respectively, using conventional PID and neural network self- tuning PID control strategy the theoretical analysis and simulation studies the performance of the system . Once again, the the application LabVIEW graphical software programming computer control of the system . Conventional PID and neural network self-tuning PID two different control strategies , experimental study comparing the performance of the system . The theoretical analysis and experimental results show that : neural network self- tuning PID control can effectively improve the dynamic quality of the system , the control strategy highlights the advantages of dynamic quality to improve the control system .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > General Automation System > Fluid Systems > Hydraulic system
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