Quick-return servomechanism with adaptive fuzzy neural network control

Rong Fong Fung, Faa Jeng Lin, Rong Jong Wai

研究成果: 雜誌貢獻期刊論文同行評審

2 引文 斯高帕斯(Scopus)


The dynamic response of an adaptive fuzzy neural network (FNN) controlled quick-return mechanism, which is driven by a permanent magnet (PM) synchronous servo motor, is described in this study. The crank and disk of the quick-return mechanism are assumed to be rigid. First, Hamilton's principle and Lagrange multiplier method are applied to formulate the mathematical model of motion. Then, based on the principle of computed torque, an adaptive controller is developed to control the position of a slider of the quick-return servomechanism. Moreover, since the selection of control gain of the adaptive controller has a significant effect on the system performance, an adaptive FNN controller is proposed to control the quick-return servomechanism. In the proposed adaptive FNN controller, an FNN is adopted to facilitate the adjustment of control gain on line. Simulated and experimental results due to periodic step and sinusoidal commands show that the dynamic behavior of the proposed adaptive FNN control system are robust with regard to parametric variations and external disturbances.

頁(從 - 到)253-264
期刊Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
出版狀態已出版 - 6月 2001


深入研究「Quick-return servomechanism with adaptive fuzzy neural network control」主題。共同形成了獨特的指紋。