Carlo Novara

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About

Carlo Novara is a leading figure in nonlinear control theory and data-driven system identification, with a particular focus on model inversion techniques for complex dynamical systems. His most cited work, "Control of MIMO nonlinear systems: A data-driven model inversion approach" (2019, 13 citations), introduces a powerful framework for controlling multi-input multi-output (MIMO) nonlinear plants without requiring explicit physical models—a critical advancement for modern engineering systems. Novara’s earlier foundational paper, "Polynomial model inversion control: numerical tests and applications" (2015, 6 citations), establishes a novel control design that identifies a polynomial model of the system and inverts it online, demonstrating robust numerical efficiency across diverse applications. More recently, his experimental work "Embedded model control of networked control systems: An experimental robotic application" (2024, 2 citations) addresses pressing challenges in networked control, such as measurement delays and asynchronous command execution, which can destabilize systems without physical communication links. Collectively, Novara’s contributions bridge theoretical rigor with practical implementation, offering scalable solutions for nonlinear and networked control problems. His research is essential reading for students and engineers working on data-driven control, robotics, and cyber-physical systems.