Amir Mahdoudi

Papers

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About

Amir Mahdoudi is a researcher in control systems engineering, with a primary focus on intelligent and hybrid control strategies. His work bridges classical control theory with modern computational intelligence, particularly through the integration of fuzzy logic with established controllers. His most-cited paper, "Combined PID and LQR controller using optimized fuzzy rules" (2018, 21 citations), exemplifies this approach by developing a novel framework that merges Proportional-Integral-Derivative (PID) and Linear Quadratic Regulator (LQR) controllers, enhanced by optimized fuzzy rule bases. This contribution addresses the challenge of balancing robustness and optimality in dynamic systems, offering a practical solution for applications in robotics, automation, and mechatronics. Mahdoudi’s research is characterized by its methodological rigor and practical relevance, aiming to improve system performance under uncertainty. While his citation count reflects a growing recognition in the field, his work stands out for its clear synthesis of multiple control paradigms, making it accessible to both theorists and practitioners. His ongoing efforts continue to explore adaptive and intelligent control, positioning him as a promising voice in the evolution of next-generation control systems.