Self-learning Control of Load Changes in Motor-driven Load Simulator Using CMAC
How to retain the high load precision of a motordriven 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 nonlinearity, 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.
motor-driven load simulator CMAC neural network load gradient PID control method load precision
Li Jianfu Fu Wenxing
College of Astronautics Northwestern Polytechnical University Xian,China
国际会议
上海
英文
156-159
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）