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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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Identifying and validating models for complex structures featuring nonlinearity remains a cutting-edge challenge in structural dynamics, with applications spanning civil structures, microelectronics
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nonlinear control and optimisation to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation
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, intermittent behaviour of renewable generation but also social aspects and market structures related to how we use electricity, increase uncertainty. Power systems are inherently nonlinear dynamical systems
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, artificial neural networks and bio-inspired robotics: "Rhythmic-reactive regulation for robotic locomotion" (Supervisor: Prof Fulvio Forni) will apply techniques from nonlinear control and optimisation
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Profile: We seek someone with strong mathematical maturity in control theory, dynamical systems, or applied mathematics. Familiarity with nonlinear systems analysis, graph theory, and formal methods (e.g
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explore the nonlinear structural dynamics of LGSs to fully understand the complexity of their control. They will use this foundation to explore idealised and realistic control laws to virtually “stiffen
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dynamically managing power flow, improving system flexibility, and mitigating transmission constraints. However, conventional methods for PST deployment often consider sizing, placement, and control in
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engines. The variable rotation speeds, complex loading and operating conditions cause significant blade vibrations. These vibrations, if not properly controlled and reduced, can lead to premature blade
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control of the electrical power system for aircraft applications, ensuring system stability across a wide range of nonlinear loads and operating conditions. Aim You will have the opportunity to research and