Papers
36
Total Citations
472
H-Index
13
About
Mohamed Tadjine is a distinguished researcher whose work spans robotics, control systems, and intelligent automation. His research career is defined by pioneering contributions to mobile robot navigation, manipulator control, and nonlinear systems stabilization — areas where he has consistently pushed the boundaries of both theory and practical application. Tadjine's early landmark contributions focused on nonholonomic systems, with his invariant manifold approach for stabilizing chained systems — applied to mobile and car-like robots — earning sustained recognition across the control engineering community (57 combined citations). This theoretical foundation complemented his parallel work on intelligent navigation, where he developed fuzzy logic and reinforcement learning frameworks enabling robots to navigate unknown environments without becoming trapped in local minima, garnering over 50 citations across multiple studies. His research evolved toward increasingly sophisticated challenges, including vision/force control of parallel robots (36 citations), redundant manipulator trajectory tracking with obstacle avoidance (59 citations), and fault estimation for nonlinear systems using adaptive observers (25 citations). More recently, his integration of type-2 fuzzy logic with wheel-slip dynamics and grey wolf optimization algorithms demonstrates his commitment to robust, real-world robotic performance. With a portfolio exceeding 300 cumulative citations, Tadjine stands as a significant voice in intelligent robotics and nonlinear control, offering researchers a rich body of work bridging rigorous mathematics with applied autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2Vision/force control of parallel robots36 citations · 2011
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