基于Quanser实验平台的带有输出约束单连杆柔性机械臂的神经网络控制

机械臂在航空航天、服务等领域的应用越来越广泛，其研究也越来越深入.相比于刚性机械臂，柔性机械臂质量轻、能耗小，具有更好的性能.但是，由于柔性机械臂本身的结构与材料具有特殊性，其在运动过程中会产生弹性形变与振动，这就给机械臂的定位、轨迹跟踪带来了困难，因此对其振动抑制的研究具有重要意义.本文利用假设模态法对单连杆柔性机械臂系统进行建模，通过李雅普诺夫直接法实现了闭环系统的稳定性.由于一些实际问题对控制系统的状态量有特殊要求，因此采用正切函数形式的障碍李雅普诺夫策略来处理输出约束问题，之后利用神经网络控制方法来逼近系统的不确定性，通过李雅普诺夫法对闭环系统的稳定性进行了分析，并基于Matlab平台设计仿真、基于Quanser实验平台进行实验，对控制器的控制性能进行了验证.

Neural network control of a single-link flexible manipulator with output constraints based on Quanser platform

Owing to their rapidly increasingapplicationsin aerospace,service,and other fields,manipulators are an area of active in-depth research.In comparison with the rigid manipulator,the flexible manipulator is light,flexible,and highly efficient.It also consumes less energy.The advantages of the flexible manipulator have made it a subject of in-depth study and further research.However,because of the particularity of the structure and build material,the operation of the flexible manipulator produces elastic deformation and vibration,which make the positioning and tracking of the manipulator difficult.Thus,it is important to study vibration suppression.In this paper,the assumed mode method is used to model the single-link flexible manipulator system andthe Lyapunov direct method is used to realize the stability of the closed-loop system.Giventhe particular constrained targets in practical use,the tangent-function form of the Lyapunov strategy is utilized to deal with the output constraints.The neural network control method is used to approach the uncertainty of the system,and the stability of the closed-loop system is analyzed by the Lyapunov method.The control performance of the controller is verified through simulations in MATLAB and experiments using the Quanser platform.