典型文献
Adaptive neural network based boundary control of a flexible marine riser system with output constraints
文献摘要：
In this study,we develop an adaptive neural network based boundary control method for a flexible marine riser system with unknown nonlinear disturbances and output constraints to suppress vibrations.We begin with describing the dynamic behavior of the riser system using a distributed parameter system with partial differential equations.To compensate for the effect of nonlinear disturbances,we construct a neural network based boundary controller using a radial basis neural network to reduce vibrations.Under the proposed boundary controller,the state of the riser is guaranteed to be uniformly bounded based on the Lyapunov method.The proposed methodology provides a way to integrate neural networks into boundary control for other flexible robotic manipulator systems.Finally,numerical simulations are given to demonstrate the effectiveness of the proposed control method.
文献关键词：
中图分类号：
作者姓名：
Chuyang YU;Xuyang LOU;Yifei MA;Qian YE;Jinqi ZHANG
作者机构：
Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),Jiangnan University,Wuxi 214122,China;College of Internet of Things Technology,Wuxi Institute of Technology,Wuxi 214121,China;Wuxi Good Cloud IoT Technology Co.,Ltd.,Wuxi 214196,China
文献出处：
引用格式：
[1]Chuyang YU;Xuyang LOU;Yifei MA;Qian YE;Jinqi ZHANG-.Adaptive neural network based boundary control of a flexible marine riser system with output constraints)[J].信息与电子工程前沿（英文）,2022(08):1229-1238
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B类：
Adaptive,neural,boundary,flexible,marine,riser,output,constraints,In,this,study,we,develop,adaptive,unknown,nonlinear,disturbances,suppress,vibrations,We,begin,describing,dynamic,behavior,using,distributed,parameter,partial,differential,equations,To,compensate,construct,controller,radial,basis,reduce,Under,proposed,state,guaranteed,uniformly,bounded,Lyapunov,methodology,provides,way,integrate,networks,into,other,robotic,manipulator,systems,Finally,numerical,simulations,are,given,demonstrate,effectiveness
AB值：
0.526702
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