Hussain Alazki
Papers
9
Total Citations
73
H-Index
6
About
Hussain Alazki’s research focuses on robust control theory and its application to complex, uncertain robotic and mechatronic systems. His core contributions lie in developing advanced sliding mode control strategies, including integral sliding mode and super-twisting algorithms, often integrated with convex optimization techniques like the Attractive Ellipsoid Method (AEM). Alazki has tackled challenging problems across a diverse range of platforms, from flexible-arm robots and industrial manipulators (including a real-time 5-DOF implementation) to unmanned surface vehicles navigating marine disturbances. His work on integral sliding mode convex optimization for uncertain Lagrangian systems, which has garnered 21 citations, exemplifies his approach of combining rigorous mathematical frameworks with practical control design. More recently, he has extended his methods to multi-robot systems with Markov-chain-based decision-making and sensorless motion control for manipulators under external forces. By addressing real-world challenges such as payload changes, torque disturbances, and noisy measurements, Alazki’s research provides robust, implementable solutions that bridge the gap between theoretical control theory and autonomous robotic operation.
Research Focus
Key Achievements
Top Papers
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- 3Robust bounded control for the flexible arm robot9 citations · 2013
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- 6Super Twisting Control For Thermo’s Catalyst-5 Robotic Arm7 citations · 2018
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