Dissertation > Excellent graduate degree dissertation topics show

Design of Weapon Detection Device Control System

Author: OuYangBin
Tutor: ZhuZuo
School: Harbin Institute of Technology
Course: Control Science and Engineering
Keywords: servo system neural network control RBF inverse models
CLC: TP183
Type: Master's thesis
Year: 2008
Downloads: 51
Quote: 0
Read: Download Dissertation


Servo System detection device is a system that test indicators of servo system. How to improve loading accuracy in the device is key issue of Servo system detection device.The loading motor follows the position changes of the rudder passively and so the influence of redundancy torque becomes inevitably which is the mutual problem of passive systems. As a kind of intense disturbance, the redundancy torque effects the loading precision and the dynamic performance badly and can’t be controlled by conventional control strategy based on accurate model. Aiming at the problem of redundancy torque, this paper presents a new kind of inverse model control strategy based on RBF neural networks. Using the excellent nonlinear function approximation of RBF neural network, the identification neural network identify the inverse model of the object on real-time, and it’s copy is put into the forward channel of the system as a forward compensation controller. Ideally, the transfer function of forward channel close to 1,the output would follow the order accurately.Firstly, the mathematic model of the system is obtained and the effect of the redundancy torque is analyzed via simulation.Then a control method based on traditional forward feedback method is used in designing the control method of system, and we point out inadequate of this method Subsequently, an improved RBF arithmetic is proposed too, which is generated offline and updated online. By fully using the existed knowledge of the object and optimizing the network parameter locally, the calculating burden and the size of network are observably lessened.The simulation analyzing is carried out in the Matlab/Simulink environment, the simulation result show that the proposed control strategy can restrain the redundancy torque effectively, improve the dynamic performance and loading precision under different loading frequency and different loading grads.

Related Dissertations

  1. Research on Gyro Stabilized and Tracking Platform,V241.5
  2. Several Key Issues on Closed-Loop Control for Precision Laser Tracking Device,TN249
  3. Research on the Synchronous Control Algorithm of a Special Target Simulator,TP273
  4. Sliding Mode Variable Tructure Control for Separating-Mirror System and Inhibit Chattering,TP273
  5. Study of Synchronous Generator Excitation Control Based on Neural Network Identification,TM31
  6. The Identification of Fault Type in Transmission Lines Based on Neural Network,TP183
  7. Study on Risk Identification and Evaluation of Manufacturing Green Products R & D,F205;F224
  8. Based on Neural Network Model of Hot-rolling,TP183
  9. Research of Software Way for Canopen-protocol’s Realization and Implantation in Servo System,TP273
  10. Study on Properties of Compound Dynamic Damper,TB535.1
  11. Aerocraft Simulator Servo System Controlling & Parameter Tuning Techniques,V249.1
  12. Based on RBF artificial neural network in the application of PCB drilling process,TN405
  13. Networked Control System Fault Diagnosis and Fault Tolerant Control,TP273
  14. Linear guide system Elevator single electromagnetic levitation RBF neural network sliding mode control,TP273
  15. Optimization algorithm based on artificial intelligence Melt Index Prediction Modeling Optimization,TQ325.14
  16. Based on Virtual Instrument Simulation Load Test System Design,TP274
  17. Linear Servo System Based on thermoacoustic engine output characteristic simulation study,TM301
  18. Optical freeform surface shape description method and ray tracing model of,O435
  19. Robust and adaptive unmanned helicopter Tolerant Control Technology,V249.1
  20. Planning for weapon delivery Adaptive Hybrid Response Surface Optimization Method,V271.4

CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
© 2012 www.DissertationTopic.Net  Mobile