發(fā)布時(shí)間：2018-06-12 01:22

  本文選題：神經(jīng)網(wǎng)絡(luò) + X-Y定位平臺(tái)��； 參考：《機(jī)械設(shè)計(jì)與制造》2015年12期

【摘要】：針對X-Y定位平臺(tái)中摩擦等非線性部分對控制精度的影響問題,提出了基于自適應(yīng)神經(jīng)網(wǎng)絡(luò)的魯棒控制策略。設(shè)計(jì)神經(jīng)網(wǎng)絡(luò)控制器對摩擦及干擾等不確定部分進(jìn)行補(bǔ)償,其網(wǎng)絡(luò)逼近誤差作為外界擾動(dòng)通過魯棒控制器消除,保證X-Y平臺(tái)的定位精度;設(shè)計(jì)神經(jīng)網(wǎng)絡(luò)參數(shù)學(xué)習(xí)算法,保證權(quán)值的在線自適應(yīng)實(shí)時(shí)調(diào)整�；贖∞的HJI理論證明了控制系統(tǒng)的穩(wěn)定性,并保證了系統(tǒng)L2增益小于給定的指標(biāo)。試驗(yàn)結(jié)果表明所提控制方法能夠很好補(bǔ)償摩擦模型,提高了定位精度,具有重要工程應(yīng)用價(jià)值。
[Abstract]:A robust control strategy based on adaptive neural network is proposed to solve the problem of the influence of nonlinear parts such as friction on the control accuracy of X-Y positioning platform. The neural network controller is designed to compensate the uncertain parts such as friction and disturbance. The network approximation error is eliminated by the robust controller as the external disturbance to ensure the location accuracy of X-Y platform, and the neural network parameter learning algorithm is designed. Online adaptive real-time adjustment of weights is guaranteed. The HJI theory based on H 鈭，

本文編號：2007599