PhD Position Chaotic Sampling for Secure and Sustainable Networked Control Systems

Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems. Job description Wireless communication can make control systems cheaper and easier to deploy, but bandwidth and energy limitations, as well as vulnerability to cyber-attacks, restrict its use in critical applications. Event-based control approaches can greatly reduce communication by transmitting information only when required, while potentially generating complex, chaotic sampling patterns. This project investigates how such patterns can be designed systematically to make communication timing difficult for an external observer to predict, while maintaining closed-loop stability and using network resources efficiently. In this PhD project, you will develop mathematical theory and computational methods for the analysis and design of chaotic sampling mechanisms in networked control systems. You will study conditions under which event-based sampling exhibits chaotic behavior and how to design controller and sampler strategies that account for stability, communication rate, and measures of timing unpredictability such as entropy. You will also investigate the robustness of these mechanisms to disturbances and assess whether transmission patterns can be learned from external observations. This position is part of a new lab at the Delft Center for Systems and Control, supervised by Gabriel de Albuquerque Gleizer. The research will allow you to gain deep insights across nonlinear dynamics, optimization, and theoretical computer science, and to combine those in new innovative ways. The position will offer you the opportunity to work on important problems with real-world impact and a strong publication potential. As the project progresses, you will also have the freedom to contribute to an experimental demonstration using a wireless lab-scale control system. Still, this position is theory-centric: expected outcomes include theoretical results, mathematical proofs, and computational algorithms, as well as open-source software and validation through simulations and analysis. Experimental demonstration is an option if it interests you. Teaching activities are part of your PhD trajectory and may include, for example: supervising workgroups or lab sessions, assisting in courses, or mentoring BSc and MSc students. While teaching will not be your main responsibility, it offers valuable experience that supports your development and prepares you for future academic or professional roles. Teaching activities will not exceed 20% of your total appointment, averaged over the course of your PhD. Job requirements Essential • An MSc degree in systems & control, electrical engineering, mechanical engineering, applied mathematics, physics, theoretical computer science, or a closely related field. • Strong enthusiasm for mathematics and abstraction,…