C
Chun-Liang Lin
Researcher at National Chung Hsing University
Publications - 258
Citations - 3195
Chun-Liang Lin is an academic researcher from National Chung Hsing University. The author has contributed to research in topics: Control theory & Robust control. The author has an hindex of 26, co-authored 245 publications receiving 2685 citations. Previous affiliations of Chun-Liang Lin include Feng Chia University & Chungshan Institute of Science and Technology.
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Industrial IoT in 5G environment towards smart manufacturing
TL;DR: The architecture of 5G-based IIoT is proposed, and the implementation methods of different advanced manufacturing scenarios and manufacturing technologies under the circumstances of three typical application modes of5G, respectively, i.e., enhance mobile broadband, massive machine type communication, ultra-reliable and low latency communication.
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GA-based multiobjective PID control for a linear brushless DC motor
TL;DR: In this paper, a robust output tracking control design method for a linear brushless DC motor with modeling uncertainties is presented, where two frequency-domain specifications directly related to the mixed sensitivity function and control energy consumption are imposed to ensure stability and performance robustness.
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On the stability bounds of singularly perturbed systems
Bor-Sen Chen,Chun-Liang Lin +1 more
TL;DR: In this article, a set of new stability conditions based on the frequency-domain representation is derived for linear time-invariant singularly perturbed systems, which can be easily verified by computing certain singular values within finite frequency intervals.
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Block-Layout Design Using MAX–MIN Ant System for Saving Energy on Mass Rapid Transit Systems
TL;DR: It is shown that the method presents a significant improvement for the reduction of computational burden on the block-layout design and the train-speed trajectory for saving energy is optimized by a MAX-MIN ant system (MMAS) of ant colony optimization (ACO) algorithms.
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Optimization of train-speed trajectory and control for mass rapid transit systems
TL;DR: Satisfactory simulation results show applicability and effectiveness of the proposed approach as a tool for designing an energy-saving mass rapid transit system.