Aadithyan Sridharan
Papers
1
Total Citations
33
H-Index
1
About
Aadithyan Sridharan is a robotics and control systems researcher whose work bridges theoretical advances with real-world implementation. His primary research areas include nonlinear model predictive control (NMPC), robotic manipulation, and quasi-LPV (Linear Parameter Varying) system representations. Sridharan’s most influential contribution is his 2018 paper, “Constrained Predictive Control of a Robotic Manipulator using quasi-LPV Representations,” which has garnered 33 citations. In this work, he developed a practical NMPC framework that successfully handles nonlinear state constraints on robotic arms by leveraging quasi-LPV modeling—a technique that simplifies complex nonlinear dynamics into a more tractable form. Critically, Sridharan validated his approach through experimental implementation on a physical manipulator, demonstrating that theoretical control algorithms can be effectively deployed in real hardware environments. This combination of rigorous control theory with experimental confirmation distinguishes his work, offering a scalable pathway for advanced automation in manufacturing and robotics. His research continues to impact the field by providing engineers with computationally efficient yet robust control strategies for constrained robotic systems.
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