Lotfi Messikh

Papers

Total Citations

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About

Lotfi Messikh is a robotics and control systems researcher whose work focuses on the advanced motion control of robotic manipulators. His most cited contribution, "Model predictive control of a two-link robot arm" (2018, 24 citations), introduces a novel hybrid control strategy that combines feedback linearization with model predictive control (MPC) to manage the complex nonlinear dynamics of robotic arms. By first linearizing the nonlinear dynamic model, Messikh enables the application of predictive control, allowing for more precise trajectory tracking and improved disturbance rejection in real-time operations. This work addresses a fundamental challenge in robotics: balancing computational efficiency with high-performance control. While his citation count reflects a growing, specialized impact, Messikh’s approach is particularly notable for its practical applicability to industrial and service robotics, where two-link arms are common. His research bridges theoretical control theory and practical implementation, offering a scalable framework that can be extended to more complex robotic systems. For students and researchers in robotics, Messikh’s work exemplifies how classical control techniques can be modernized with predictive algorithms to enhance robotic autonomy and precision.