Control of the Electric Load Simulator Using Fuzzy Multiresolution Wavelet Neural Network with Dynamic Compensation

A fuzzy multiresolution wavelet neural network (FMWNN) controller with dynamic compensation (DC) is proposed to address the complexities of the electric load simulator (ELS). The FMWNN acts as a main torque tracking controller, which takes full advantage of the merits of an ideal sliding mode, fuzzy...

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Bibliographic Details
Published inShock and vibration Vol. 2016; no. 2016; pp. 1 - 10
Main Authors Gao, Qiang, Liu, Rongzhong, Hou, Yuan-long, Wang, Chao, Hou, Runmin
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 01.01.2016
John Wiley & Sons, Inc
Hindawi Limited
Subjects
Algorithms
Compensation
Computer simulation
Control algorithms
Control systems
Controllers
Fault tolerance
Firearm laws & regulations
Fuzzy
Fuzzy logic
Guarantees
Loads (forces)
Neural networks
Systems stability
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Summary:A fuzzy multiresolution wavelet neural network (FMWNN) controller with dynamic compensation (DC) is proposed to address the complexities of the electric load simulator (ELS). The FMWNN acts as a main torque tracking controller, which takes full advantage of the merits of an ideal sliding mode, fuzzy rules, and multiresolution WNN. The fuzzy algorithm is used to dynamically adjust the weights of the WNN and effectively accelerate the convergence rate. In addition, the DC controller is designed to greatly decrease the effect of the approximation error and guarantee the system stability in the sense of the Lyapunov theory. Finally, the proposed algorithms are carried out on the semiphysical simulation platform, the precision and superiority of which are comparatively verified based on the simulation results.
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ISSN:1070-9622
1875-9203
DOI:10.1155/2016/3574214