Enhancing Design of Visual-Servo Delayed System  

作　　者：Zhi-Ren Tsai Yau-Zen Chang 

机构地区：[1]the Department of Computer Science and Information Engineering, Asia University [2]the Department of Medical Research, China Medical University Hospital, China Medical University [3]the Department of Mechanical Engineering, Chang Gung University [4]the Department of Neurosurgery, Chang Gung Memorial Hospital

出　　处：《Journal of Electronic Science and Technology》2018年第3期232-240,共9页电子科技学刊（英文版）

基　　金：supported by MOST under Grants No.104-2632-B-468-001,No.103-2221-E-468-009-MY2,No.104-2221-E-182-008-MY2,No.105-2221-E-468-009,No.106-2221-E-468-023,and No.106-2221-E-182-033;Chang Gung Memorial Hospital,under Grants No.CMRPD2C0052 and No.CMRPD2C0053

摘　　要：A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network(RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative(PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization(PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network(RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative(PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization(PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.

关 键 词：Parallel particle swarm optimization robust adaptive predictor stereo-vision servo time-varying delay 

分 类 号：TN01[电子电信—物理电子学]