Abstract
In this study, a coupled elastic join-flexible load drive system is presented, which takes the flexibility, friction torque, and the grasping object mass in flexible manipulators into account simultaneously. These nonlinear factors lead to lumped uncertainties in dynamic modeling, which aggravates the deterioration of flexible manipulators’ rotation accuracy. Besides, a control strategy mixing neural network identification with a sliding mode controller is proposed to enhance the rotation accuracy. Firstly, based on the new deformation description method and Lagrange principle, the dynamic model of the coupled drive system is presented. Then, the deformation characteristics of the coupled drive system are analyzed, which shows that the new deformation description method can improve the modeling accuracy, and its calculation is simple. Next, the control law and adaptive law of the control strategy that uses neural networks to compensate for the lumped uncertainties are designed according to Lyapunov's theorem. Finally, some comparative simulations and prototype experiments are conducted to statistic the superiority of the proposed control strategy.
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