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The RBF-ARX Model-based Nonlinear System Modeling and Predictive Control to Magnetic Levitation System

Author: ZengQi
Tutor: PengHui
School: Central South University
Course: Control Science and Engineering
Keywords: Levitation device RBF-ARX model LQR controller Real-time control Predictive Control
CLC: TP13
Type: Master's thesis
Year: 2011
Downloads: 55
Quote: 1
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Abstract


With the improvement of the level of urbanization , many cities are built underground , but because of its cost is too expensive , policymakers actually consider maglev train . In fact, the maglev technology is only used in maglev trains outside the magnetic suspension balance, magnetic bearings , magnetic motors and other fields are also great worthiness . But the maglev system nonlinearity, open loop instability , uncertainty and other features make it not easy to control , and explore an accurate, practical control method is very valuable . In this thesis, a set of two degrees of freedom of the laboratory suction floating levitation device is expanded research , first introduced the maglev research status , the introduction of the suspension system of the physical model , RBF-ARX model , LQR theory and basic knowledge of predictive control principle, etc. after the system using the PID controller preliminary control, acquisition get the global dynamic input and output data , which is calculated maglev system RBF-ARX model, and further use of LQR controller system for real-time control , and finally , the use of magnetic levitation system RBF-ARX model state space form of expression designed predictive control strategy, simulation run and complete papers. Paper relates to the selection of many parameters in this article for each parameter selection and optimization strategies are given a detailed explanation , some based on the theoretical results , some after repeated testing concluded that all the work in order to get a better effective control effect or simulation results service . The final results show that , RBF-ARX model maglev system has a very good ability to describe ; rather based on RBF-ARX model LQR controller in real-time control achieved excellent results, on the steady-state and dynamic suspension system has a very good control effect ; in predictive control simulation also verified based on RBF-ARX model predictive controller has a good performance. I hope this article on the actual industrial process control , serve , and this excellent model to more practical industrial systems were to go.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Automatic control theory
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