Papers
11
Total Citations
137
H-Index
6
About
Khaled S. Hatamleh is a researcher specializing in estimation theory, nonlinear control systems, and robotics, with a particular focus on developing advanced filtering techniques for robotic manipulators and autonomous systems. His most influential contributions center on the application of sigma-point Kalman filters — including the Unscented Kalman Filter (UKF), Cubature Kalman Filter (CKF), and Central Difference Kalman Filter (CDKF) — to address the challenges of noisy feedback and system disturbances in industrial robotic arms, accumulating over 55 citations across these core works. A defining thread in his research is the Smooth Variable Structure Filter (SVSF), which he has combined with sliding mode control to deliver robust, accurate state estimation under modeling uncertainties, notably demonstrated in his PRRR robotic arm studies. Hatamleh has also made early contributions to UAV dynamics modeling and parameter identification, reflecting a broader interest in autonomous systems. His more recent work extends to aerial manipulators designed for practical applications such as solar panel cleaning, and intelligent fractional-order controllers for mobile robot trajectory tracking, demonstrating a continued drive to bridge theoretical estimation frameworks with real-world engineering solutions.
Research Focus
Key Achievements
Top Papers
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- 4ROBUST NONLINEAR CONTROL AND ESTIMATION OF A PRRR ROBOT SYSTEM23 citations · 2019
- 5A UAV MODEL PARAMETER IDENTIFICATION METHOD: A SIMULATION STUDY13 citations · 2009
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- 7In-Flight UAV Model Parameter Identification: A Simulation Study5 citations · 2009
- 8Application of SMC and NLFC Into a PRRR Robotic Arm3 citations · 2014
- 9Modeling and simulation of a moving robotic arm mounted on wheelchair3 citations · 2017
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