Mojtaba Ahmadieh Khanesar
Technical University of Denmark, K.N.Toosi University of Technology, University of Nottingham, Semnan University
Papers
9
Total Citations
238
H-Index
7
About
Dr. Mojtaba Ahmadieh Khanesar is a leading researcher at the intersection of intelligent control systems, robotics, and Industry 4.0, whose work is distinguished by the innovative fusion of fuzzy logic, sliding mode control, and metaheuristic optimization. His most impactful contribution is the development of a type-2 fuzzy neural network tuned by a hybrid particle swarm optimization-sliding mode control algorithm, applied to an aerial robot for rice farm quality inspection—a study that has garnered 89 citations and exemplifies his focus on robust, real-world automation. Dr. Khanesar has also made foundational theoretical advances, such as his 2011 work on Direct Model Reference Takagi–Sugeno Fuzzy Control (62 citations), which relaxed restrictive conditions on reference models for nonlinear systems. His research consistently addresses critical challenges in industrial robotics, including inverse kinematics via Extended Kalman Filters, static friction modeling using neural networks, and the integration of Ant Colony Optimization for digital twin programming. By bridging advanced control theory with practical manufacturing needs, Dr. Khanesar’s work—spanning sliding mode fuzzy control, type-2 fuzzy systems, and swarm intelligence—has become essential reading for engineers and researchers developing autonomous, adaptive, and resilient robotic systems for the factories of the future.
Research Focus
Key Achievements
Top Papers
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- 2Direct Model Reference Takagi–Sugeno Fuzzy Control of SISO Nonlinear Systems62 citations · 2011
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- 8Subspace identification of dynamical neurofuzzy system using LOLIMOT5 citations · 2010
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