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Pang-Jung Liu,Yu-Chi Hsu,Ting-Yu Wei,Zhi-Yuan Hong 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5
This paper presents a dc-dc converter with selfregulated output voltage (SROV) and phase shift PWM (PSPWM) control methods for multiple LED strings. The LED driver is composed of a boost converter and dimmable current balancing regulators (CBRs). Compared with traditional linear current regulator, the CBR is adopted to reduce power consumption. To keep a designed constant voltage on the CBRs, the output voltage of the boost converter is dynamically adjusted with the SROV control method. It results in high efficiency and current balance of the CBRs and prevents output voltage oscillation. The PSPWM control is employed to mitigate the output current variation supplied by the boot converter, leading to smaller output transient ripple when the PWM dimming signals are changed. The CBRs and control circuits were fabricated with a 0.35-μm standard CMOS technology. The experimental results demonstrate the theoretical analysis of the proposed LED driver.
Grey Neural Network-Based Forecasting System for Vision-Guided Robot Trajectory Tracking
Shih-Hung Yang,Chung-Hsien Chou,Chen-Fang Chung,Wen-Pang Pai,Tse-Han Liu,Yung-Sheng Chang,Jung-Che Li,Huan-Chan Ting,Yon-Ping Chen 제어로봇시스템학회 2011 제어로봇시스템학회 국제학술대회 논문집 Vol.2011 No.10
This paper presents a grey neural network-based forecasting system (GNNFS) in solving the prediction problem. GNNFS adopts a grey model to predict the signal and a neural network (NN) to forecast the prediction error of the grey model. A sequential batch learning (SBL) is developed to adjust the weights of the NN. The proposed GNNFS is applied to a binocular robot, called an Eye-Robot, for human-robot interaction which involved predicting the trajectory of a participant’s hand and tracking the hand. By applying the SBL, the GNNFS can gradually learn to predict the trajectory of the hand and track it well. The experimental results show that the GNNFS can carry out the SBL in real-time for vision-guided robot trajectory tracking.