Sjirk Koekebakker

Delft University of Technology, Canon (Netherlands)

Papers

Total Citations

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About

Sjirk Koekebakker is a control systems researcher whose work bridges classical model-based methods and modern data-driven techniques. His research focuses on precision motion control, particularly for complex electromechanical systems such as Stewart platforms and hybrid stepper motors. Koekebakker’s early contribution, "Coordinate Reconstruction in Model Based Control of a Stewart Platform" (1998), laid foundational work in kinematic control for parallel manipulators. More recently, he has pioneered the integration of physics-guided neural networks with inversion-based feedforward control, as demonstrated in his 2023 paper on hybrid stepper motors. This work addresses the industrial need for higher productivity and efficiency without escalating manufacturing costs, offering innovative control designs for rotary motors used in printing and robotics. While his citation counts are modest—3 and 2 respectively—his research trajectory shows a thoughtful evolution from theoretical model-based control to practical, AI-enhanced solutions. Koekebakker’s work is particularly relevant for researchers and engineers seeking to combine physical principles with machine learning for real-time control applications, making him a notable figure in the field of advanced motion control.