Chia-Der Chang

Papers

Total Citations

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About

Chia-Der Chang is a robotics and control systems researcher whose work centers on intelligent controller design for mobile robots. His primary research areas include hybrid control systems, fuzzy logic, neural networks, and genetic algorithm optimization for autonomous navigation. Chang’s most significant contribution is the development of a hybrid Fuzzy PID controller that combines traditional PID stability with fuzzy logic adaptability, achieving faster steady-state response in mobile robot movement—demonstrated on the MSI Ihomer robot and earning 28 citations. He further advanced this work by introducing genetic algorithm-based parameter tuning, which automates the optimization of hybrid intelligent controllers, and by designing an Adaptive Neural Fuzzy Inference System (ANFIS) controller that leverages self-learning capabilities to outperform conventional PID and fuzzy approaches. Through these studies, Chang has shown how intelligent, adaptive control can significantly enhance mobile robot performance in industrial automation contexts. His research, published between 2018 and 2019, has accumulated over 50 citations, reflecting its relevance to the growing field of autonomous systems. Chang’s work provides a practical pathway for integrating machine learning into real-time robot control, making him a notable contributor to intelligent robotics.