Papers
1
Total Citations
6
H-Index
1
About
Anwar Shah is a pioneering researcher in the fields of robotic manipulator technology and intelligent control systems. His work bridges classical control theory with modern artificial intelligence, driving the evolution of autonomous robotic systems. Shah’s most-cited paper, "From classical to intelligent control: Evolving trends in robotic manipulator technology" (2025), has garnered 6 citations, establishing him as a forward-thinking voice in the transition from traditional PID-based approaches to adaptive, learning-driven control architectures. This contribution systematically maps the trajectory of robotic manipulation, highlighting how neural networks and fuzzy logic are reshaping precision, flexibility, and real-time decision-making in industrial and service robots. Shah’s research is pivotal for students and engineers seeking to understand the next generation of smart automation, where machines not only follow commands but learn and adapt. His work underscores a commitment to making robotics more responsive and efficient, with implications for manufacturing, healthcare, and beyond. As a rising scholar, Anwar Shah is shaping the dialogue on how intelligent control can unlock the full potential of robotic systems in an increasingly automated world.
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Top Papers
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