Bakri Shaukifeh

University of Aleppo, Moscow Institute of Physics and Technology

Papers

Total Citations

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About

Bakri Shaukifeh focuses on adaptive and optimal control strategies for robotic manipulators, particularly those operating in complex or constrained environments. His major contributions lie in developing controllers that maintain high performance despite unknown system parameters or challenging kinematic structures. In his most-cited work (2019, 10 citations), Shaukifeh introduced an adaptive LQ-based computed-torque controller for rigid two-link manipulators, combining linear quadratic optimal control with an adaptive update rule to handle dynamic model uncertainties. This work provides a practical framework for precise motion control without requiring exact parameter knowledge. More recently (2021, 2 citations), he extended adaptive control methods to manipulators with closed kinematic chains and linear actuators, specifically designed for robotic complexes servicing vertical surfaces—integrating wheeled platforms and vacuum-contact robots. This application-oriented research addresses real-world challenges in automated maintenance and inspection. Shaukifeh’s work bridges theoretical control design with practical robotic applications, offering robust solutions for manipulators operating under uncertainty. His research is particularly valuable for students and engineers working on adaptive control, robotic manipulation, and field robotics.