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Application of PID Controller based on Improved BPNN in the Magnetic Inertial Measurement System
LI Deqiang,ZHANG Yangan *
State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijng, PRC (100876)
*Correspondence author
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Funding: none
Opened online:14 January 2015
Accepted by: none
Citation: LI Deqiang,ZHANG Yangan.Application of PID Controller based on Improved BPNN in the Magnetic Inertial Measurement System[OL]. [14 January 2015] http://en.paper.edu.cn/en_releasepaper/content/4627112
 
 
To adapt slow time variation of the hardware parameters and nonlinearities in Magnetic Inertial Measurement System (MIMS), the improved Back Propagation Neural Network (BPNN) algorithm is effectively integrated to the traditional PID controller. BPNN has the ability to represent any nonlinear functions, which can achieve the best combination of PID three coefficients in real time online learning. Using BPNN can help to build the coefficient self-learning PID controller in MIMS. The simulation which was established in MATLAB indicates that the improved BPNN PID controller can improve the robustness of system and has high accuracy control. At last, experiments in MIMS convincingly verified the simulation.
Keywords:Magnetic Inertial Measurement System; Improved BPNN; PID controller
 
 
 

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