Optimal Neural-fuzzy Approach for Current/voltage-controlled Electromagnetic Suspension System
張晏誠、吳幸珍
E-mail: [email protected]
ABSTRACT
In this article, the electromagnetic suspension system is modeled as a neural-based T-S fuzzy system, and then the optimal fuzzy control design scheme is proposed to control the current and voltage-controlled system with minimum current and voltage consumption, respectively. The proposed self-constructing neural fuzzy inference network is a six layer neural network (SONFIN) modified from the well-known SONFIN network, which can construct a linear T-S fuzzy model and affine T-S fuzzy model of the system just by the input and output (I/O) information. Based on the T-S model, we can construct the optimal fuzzy control scheme to efficiently regulate the highly nonlinear, complex and uncertain electromagnetic suspension system to the equilibrium state.
Keywords: SONFIN, electromagnetic suspension system, optimal fuzzy control Keywords : SONFIN ; optimal fuzzy control ; electromagnetic suspension system
Table of Contents
CHAPTER 1 INTRODUTION ...1 1.1 Motivation ...1 1.2 Review Literature ...2 1.3 Survey of Fuzzy Model ...2 1.4 Survey of Fuzzy Control ...3 1.5 Brief Sketch of the Contents ...5 CHAPTER 2 ELECTROMAGNETIC SUSPENSION SYSTEM ...6 2.1 Construction ...6 2.2 Mathematical Model ...7 CHAPTER 3 NEURAL
NETWORK BASED FUZZY MODELING ...12 3.1 Takagi and Sugeno’s Fuzzy Model ...12 3.2 Linear T-S Fuzzy Model and Affine T-S Fuzzy Model ...13 3.3 Structure of SONFIN ...15 3.4 T-S Fuzzy Modeling of Electromagnetic Suspension System 20 CHAPTER 4 OPTIMAL FUZZY CONTROL DESIGN ...26 4.1 Local Concept Approach of Linear T-S Fuzzy Model ...26 4.2 Local Concept Approach of Affine T-S Fuzzy Model ...30 CHAPTER 5 INTEGRATION OF FUZZY SYSTEM MODELING AND OPTIMAL CONTROLLER DESIGN
...32 5.1 Numeral Simulation ...33 5.2 Simulated Results of The Robustness ...43 CHAPTER 6 CONCLUSION ...51 REFERENCE ...53 REFERENCES
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