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About

Mina Salim is a leading researcher in the field of advanced robotics and nonlinear control systems, with a primary focus on data-driven control strategies for robotic manipulators and exoskeletons. Her work is distinguished by pioneering contributions to model-free adaptive control, particularly through the integration of terminal sliding mode techniques with iterative learning and predictive control frameworks. Salim’s most cited paper (2021, 26 citations) introduces a model-free adaptive iterative learning integral terminal sliding mode controller for exoskeleton robots, addressing reference tracking under external perturbations without requiring prior system models. Her earlier work (2019, 15 citations) develops a data-driven observer-based controller for rigid robot manipulators, while another study (2019, 6 citations) extends these methods to pneumatic artificial muscle-driven systems. Additionally, her comparative study on PID controller design for Gryphon robots using evolutionary algorithms (2010, 5 citations) demonstrates her versatility in optimization-based control. Collectively, Salim’s research has garnered significant attention, with her data-driven approaches offering robust, model-free solutions that are highly relevant for real-world robotic applications where system dynamics are uncertain or difficult to model.