Adaptive NN Control for a Flexible Manipulator With Input Backlash and Output Constraint
Zhijia Zhao, Kaili Feng, Xiaowei Wang, Chenguang Yang, Xing Li, Keum‐Shik Hong
Abstract
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.
Topics & Concepts
BacklashConstraint (computer-aided design)Control theory (sociology)Manipulator (device)Adaptive controlComputer scienceControl (management)Control engineeringEngineeringArtificial intelligenceRobotMechanical engineeringAdaptive Control of Nonlinear SystemsIterative Learning Control SystemsControl Systems in Engineering