Mohammad Akbari

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About

Dr. Mohammad Akbari is a leading researcher in advanced robotics and intelligent control systems, with a particular focus on the modeling and stabilization of flexible joint robots. His work masterfully integrates Takagi–Sugeno (T-S) fuzzy logic with evolutionary optimization, addressing the critical challenge of controlling highly nonlinear and underactuated robotic systems. His most influential paper, "Improved Takagi–Sugeno fuzzy model-based control of flexible joint robot via Hybrid-Taguchi genetic algorithm" (2014, 33 citations), introduced a novel hybrid optimization technique that combines Taguchi methods with genetic algorithms to fine-tune fuzzy controllers, achieving superior tracking performance and vibration suppression. In his foundational 2012 study (12 citations), Dr. Akbari pioneered the use of sum-of-squares (SOS) stability analysis for T-S fuzzy models of flexible joints, providing rigorous mathematical guarantees for system stability—a significant leap from traditional linearization approaches. By fusing chaos theory with distributed genetic algorithms and Hermite–Biehler stability criteria, he has created a robust framework for real-time control of complex robotic manipulators. His contributions are essential reading for researchers in nonlinear control, soft computing, and mechatronics, offering practical solutions for next-generation lightweight and flexible robots.