Vibration Control of a Flexible Robotic Manipulator in the Presence of Input Deadzone
By Wei He, Yuncheng Ouyang, Jie Hong. IEEE Transactions on Industrial Informatics, 2017
370 citations recorded by the source corpus.
In this paper, a neural network (NN) controller is designed to suppress the vibration of a flexible robotic manipulator system with input deadzone. The NN aims to approximate the unknown robotic manipulator dynamics and eliminate the effects of input deadzone in the actuators. In order to describe the system more accurately, the model of the flexible manipulator is constructed based on the lumping spring-mass method. Full state feedback NN control is proposed first and output feedback NN control with a high-gain observer is then devised to make the proposed control scheme more practical. The effect of input deadzone is approximated by a radial basis function neural network (RBFNN) and the unknown dynamics of the manipulator is approximated by another RBFNN. The proposed NN control is able to compensate for the estimated deadzone effect and track the desired trajectory. For the stability analysis, the Lyapunov's direct method is used to ensure uniform ultimate boundedness (UUB) of the closed-loop system. Simulations are given to verify the control performance of the NN controllers comparing with the proportional derivative (PD) controller. At last, the experiments are conducted on the Quanser platform to further prove the feasibility and control performance of the NN controllers.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/c0879249c718f3a3be35848070a782155e1a9c2d
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In Control and Systems Engineering
Citations in the corpus
- Leader–Follower Formation Control of USVs With Prescribed Performance and Collision Avoidance (2019, methodology): “Based on the dynamic surface control (DSC) technique [27]–[29], the PPC methodology [21], adaptive control techniques [30]–[32], neural network (NN) approximators [33]– [37], the backstepping procedure, and the Lyapunov synthesis, we propose decentralized leader–follower formation control that guara”