A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parame...A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parameters and a directly friction state variable The dynamic structured Fuzzy Neural Network （RFNN） is designed to give additional robustness to the cantrol system under the presence of the friction model uncertainty. A proposed composite cantrol scheme is applied to the position tracking control of the servo systen. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.展开更多
针对直线电机易受诸多不确定因素的影响,提出了采用递归模糊神经网络和扰动观测器的控制方案。系统采用 IP 位置控制器;扰动观测器将所观测的扰动力前馈,提高了系统的抗干扰能力。为改善系统受到突加减扰动时的伺服性能,引进了递归模糊...针对直线电机易受诸多不确定因素的影响,提出了采用递归模糊神经网络和扰动观测器的控制方案。系统采用 IP 位置控制器;扰动观测器将所观测的扰动力前馈,提高了系统的抗干扰能力。为改善系统受到突加减扰动时的伺服性能,引进了递归模糊神经网络补偿器,采用动态反馈学习算法,在线调整。仿真结果表明,该控制方案可以有效增强系统的鲁棒性。展开更多
To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） s...To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.展开更多
基金supported by Ministry of Knowledge and Economy,Koreathe ITRC(Information Technology Research Center)support program(ⅡTA-2009-C1090-0902-0004)
文摘A nonlinear dynamic friction control is dealt with using dynamic friction observer and intelligent cantrol. The adaptive dynamic friction obsrver based on the LuGre friction is proposed to estimate the friction parameters and a directly friction state variable The dynamic structured Fuzzy Neural Network （RFNN） is designed to give additional robustness to the cantrol system under the presence of the friction model uncertainty. A proposed composite cantrol scheme is applied to the position tracking control of the servo systen. The performances of the proposed friction observer and the friction controller are demonstrated by simulation.
文摘针对直线电机易受诸多不确定因素的影响,提出了采用递归模糊神经网络和扰动观测器的控制方案。系统采用 IP 位置控制器;扰动观测器将所观测的扰动力前馈,提高了系统的抗干扰能力。为改善系统受到突加减扰动时的伺服性能,引进了递归模糊神经网络补偿器,采用动态反馈学习算法,在线调整。仿真结果表明,该控制方案可以有效增强系统的鲁棒性。
基金Project supported by the National Natural Science Foundation of China (Grant No.20576071)the Natural Science Foundation of Shanghai Municipality (Grant No.08ZR1409800)
文摘To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.
