Anti-sway tracking control of tower cranes with delayed uncertainty using a robust adaptive fuzzy control

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• 作者：Tzu-Sung Wu^a ; ^{tzu-sung.wu@qatar.tamu.edu" class="auth_mail" title="E-mail the corresponding author} ; Mansour Karkoub^a ; ^{mansour.karkoub@qatar.tamu.edu" class="auth_mail" title="E-mail the corresponding author} ; Wen-Shyong Yu^b ; ^{wsyu@ctr1.ee.ttu.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Chien-Ting Chen^a ; ^{ctkgai@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Ming-Guo Her^c ; ^{mgher@ttu.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Kuan-Wei Wu^a ; ^{kuan-wei.wu@qatar.tamu.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Tower crane systems ; Adaptive fuzzy control ; H&infin ; H&infin ; control ; Variable structure scheme ; Time delays
• 刊名：Fuzzy Sets and Systems
• 出版年：2016
• 出版时间：1 May 2016
• 年：2016
• 卷：290
• 期：Complete
• 页码：118-137
• 全文大小：1041 K

文摘

Tower cranes are very complex mechanical systems and have been the subject of research investigations to reduce the swaying of the payload for several decades. Inherently, the dynamical model of the tower cranes is highly nonlinear and classified as underactuated. Also, the actuators are far from the payload which makes the system non-colocated. It is proposed here to use an class="mathmlsrc">class="formulatext stixSupport mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S0165011415000305&_mathId=si1.gif&_user=111111111&_pii=S0165011415000305&_rdoc=1&_issn=01650114&md5=53bc418805b0a6d4d41e4135f78adfd5" title="Click to view the MathML source">H_∞class="mathContainer hidden">class="mathCode">$H_{\infty }$ based adaptive fuzzy control technique to control the swaying motion of a tower crane. The advantage of employing an adaptive fuzzy system is the use of linear analytical results instead of estimating the dynamics of the tower crane with an online update law. The proposed robust control law for payload positioning is based on a variable structure (VS) adaptive fuzzy control scheme. The adaptive fuzzy control technique fuses a VS scheme and it is derived based on a Lyapunov criterion and the Riccati-inequality. The control design overcomes modeling inaccuracies, such as drag and friction losses, effect of time delays from backlash, as well as parameter uncertainties and compensate for the effect of the external disturbances on tracking error such that all the states of the system are uniformly ultimately bounded (UUB). Therefore, the class="mathmlsrc">class="formulatext stixSupport mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S0165011415000305&_mathId=si1.gif&_user=111111111&_pii=S0165011415000305&_rdoc=1&_issn=01650114&md5=53bc418805b0a6d4d41e4135f78adfd5" title="Click to view the MathML source">H_∞class="mathContainer hidden">class="mathCode">$H_{\infty }$ tracking performance can be achieved such that the payload swing is reduced to as small as possible when the payload is moved from point to point. Simulations show that the proposed control scheme is effective in reducing payload swing in the presence of uncertainties, time delays, and external disturbances.