Adaptive NN Control for a Flexible Manipulator With Input Backlash and Output Constraint
提出一种自适应逆神经网络控制方法，用于消除柔性单连杆机械臂的输入回差、逼近系统不确定性并保证输出不越界，仿真和实验验证了可行性。
This article proposes an adaptive inverse neural network (NN) control of an uncertain flexible single-link manipulator with input backlash and output constraint. First, an adaptive inverse function is applied to eliminate the input backlash of the actuator. Second, an NN is applied to approximate the system uncertainty. Third, a barrier Lyapunov function is used to guarantee that the system is maintained within the constraints. Subsequently, the system’s semi-globally uniformly ultimately bounded stability is proved by the Lyapunov direct method. Finally, the simulation and experimental results manifest the feasibility of the proposed controller.