NDLI: Self-learning control of load changes in motordriven load simulator using CMAC

Content Provider	IEEE Xplore Digital Library
Author	Li Jianfu Fu Wenxing
Copyright Year	2009
Description	Author affiliation: College of Astronautics, Northwestern Polytechnical University, Xi'an, China (Li Jianfu; Fu Wenxing)
Abstract	How to retain the high load precision of a motor-driven load simulator in the case of great change in load gradient is one of its key problems. In the past, the compound PID control method was used to improve its load precision. However, because of the influence of its time-varying character and non-linearity, the method does not produce ideal load speed or precision. Taking the characteristics of the load simulator into account, the paper applies the CMAC neural-network control structure to the load simulator and presents its control structure and algorithm. The analysis of the experimental results, given in Figs. 5 and 6 and Table 2, indicates preliminarily that our method overcomes the shortcomings of the sole use of PID control method and satisfies the requirements for high-precision in the case of great changes in load gradient.
Starting Page	156
Ending Page	159
File Size	128404
Page Count	4
File Format	PDF
ISBN	9781424447541
DOI	10.1109/ICICISYS.2009.5357751
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Load gradient Three-term control Computational modeling Educational institutions Load precision Analytical models Proportional control PID control method Torque control Neural networks CMAC neural network Pi control Control system synthesis Brain modeling Motor-driven load simulator
Content Type	Text
Resource Type	Article

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