Marina Tharayil

University of Illinois Urbana-Champaign, Palo Alto Research Center

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About

Marina Tharayil is a control systems researcher whose work focuses on advancing iterative learning control (ILC) for precision motion systems. Her key research areas include time-varying filtering techniques, robust control design, and convergence analysis for repetitive processes. Tharayil's major contribution lies in developing a time-varying Q-filter scheme for ILC, which dynamically adjusts filter bandwidth during operation. This innovation allows systems to benefit from the robustness of low-bandwidth filtering while simultaneously achieving the high-performance tracking typically associated with high-bandwidth filters—a critical capability for applications requiring both stability and precision, such as high-speed manufacturing or robotic manipulation. Her most cited work, "A time-varying iterative learning control scheme" (2004), has garnered 16 citations, establishing a foundation for adaptive learning in uncertain environments. Additional papers, including "Design and Convergence of a Time-Varying Iterative Learning Control Law" (2004) and "A Time-Varying Q-Filter Design for Iterative Learning Control" (2007), further explore causal and non-causal design aspects, demonstrating rigorous convergence properties. Tharayil's research is particularly notable for bridging theoretical robustness guarantees with practical performance demands, offering engineers a powerful tool for systems requiring rapid, precise motion under model uncertainty.