About

Mohammed Chadli is a leading figure in advanced control theory, whose work masterfully bridges the gap between robust control, fuzzy logic, and intelligent systems for complex robotics and nonlinear dynamics. His core research focuses on fault-tolerant control and adaptive optimization for safety-critical systems, from industrial robot arms to autonomous quadrotors. Chadli’s seminal 2020 paper on fault-tolerant fuzzy control for semi-Markov jump systems, with 109 citations, established a foundational framework for ensuring stability under actuator failures and incomplete mode information. His highly cited 2017 work on robust adaptive neural network control for mobile robots (89 citations) demonstrates his ability to integrate learning-based methods with real-time trajectory tracking. Further impact is seen in his 2020 predictive control strategy for hybrid actuators in industrial arms (58 citations) and his early 2011 fuzzy stabilization of quadrotors (50 citations). More recently, he has pioneered prescribed-time and singularity-free finite-time adaptive control for constrained robotic manipulators. With over 400 total citations, Chadli’s contributions are essential reading for researchers in nonlinear control, robotics, and fault-tolerant systems, offering both theoretical depth and practical, implementable solutions.

Research Focus

Key Achievements

9
H-Index
11
Papers
425
Total Citations
39
Avg Citations/Paper
🏆 Most Cited Paper
Fault-Tolerant Fuzzy Control for Semi-Markov Jump Nonlinear Systems Subject to Incomplete SMK and Actuator Failures
109 citations · 2020
📈 Most Prolific Year: 2020 (3 Papers)
🤝 Key Collaborators: 30
🏛 Institutions: Université Paris-Saclay, Université de Picardie Jules Verne, Périnatalité & Risques Toxiques, Informatique, Biologie Intégrative et Systèmes Complexes

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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