Sajjad Shoja Majidabad

University of Shahrood, University of Bonab

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About

Dr. Sajjad Shoja Majidabad is a control systems researcher whose work focuses on advanced robotic manipulation and visual servoing. His primary research areas include sliding mode control, discrete-time control systems, and image-based visual servoing (IBVS). His most notable contribution is the development of discrete-time sliding mode control strategies for robot manipulators, as demonstrated in his highly cited 2012 paper on discrete-time sliding-mode control using linear and nonlinear manifolds, which has accumulated 24 citations. This work introduced Gao's reaching law to n-link robots, providing a robust framework for handling uncertainties in robotic systems. Dr. Majidabad further advanced the field with his 2019 study on pre-compensated proportional-derivative sliding mode controllers for image-based visual servoing, achieving fast, accurate, and robust motion despite system uncertainties. His research bridges theoretical control design with practical robotic applications, offering solutions that enhance precision and reliability in automated systems. Through his work, Dr. Majidabad has made significant strides in improving the performance and robustness of robotic manipulators, making him a respected figure in the control systems and robotics community.