Nonlinear Dynamics in Unconventional Robotics: Modeling, Control, and Emergent Behaviours

About the Project

These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Please consider this before applying.

Unconventional robotic systems—including soft continuum robots, tensegrity structures, bio-inspired crawlers, and compliant legged platforms—exhibit mechanically rich behaviours arising from strong nonlinearities, distributed actuation, and complex material properties. These features enable levels of adaptability, resilience, and efficiency that exceed those of traditional rigid-body robots, but they also challenge existing modeling and control frameworks, which often rely on linear or weakly nonlinear assumptions. This PhD project aims to investigate how nonlinear dynamics fundamentally shape the motion, stability, and emergent capabilities of unconventional robots, and to develop principled methods for exploiting these dynamics to improve performance in uncertain and unstructured environments.

The project will begin by characterizing key nonlinear dynamical regimes in representative unconventional robotic systems. Through a combination of experimental studies and computational analysis, phenomena such as bifurcations, multistability, limit cycles, passive compliance, and chaotic behaviour will be identified and analyzed in soft, tensegrity, and hybrid robots. Reduced-order models will be developed to capture the essential dynamics governing these behaviours while remaining tractable for analysis and control design.

Building on this understanding, the project will develop dynamics-aware control frameworks that explicitly leverage, rather than suppress, nonlinear effects. Control strategies based on concepts such as energy shaping, limit-cycle stabilization, and morphological computation will be explored to harness intrinsic system dynamics. Learning-based components will be integrated to handle modeling uncertainty and environmental variability, while preserving stability and robustness guarantees wherever possible.

The project will further investigate emergent behaviours and morphological computation in unconventional robots. In particular, it will study how distributed elasticity, anisotropic materials, and unconventional morphologies contribute to self-organization, locomotion efficiency, and adaptive interaction with the environment. The computational role of mechanical nonlinearities will be quantified in terms of reduced control effort, improved robustness, or enhanced task performance.

All methods will be validated on physical robotic platforms, including soft continuum arms, vibro-robots, tensegrity crawlers, and flexible quadrupeds, with evaluation focused on robustness to perturbations, energetic efficiency, and functional adaptability. The outcomes will advance the theoretical and practical understanding of nonlinear dynamics in robotics, with implications for applications such as search-and-rescue, medical devices, planetary exploration, and human–robot interaction.

Decisions will be based on academic merit. The successful applicant should have, or expect to obtain, a UK Honours Degree at 2.1 (or equivalent) in degree in Electrical / Control / Mechanical / Mechatronics / Control Engineering, Applied Physics / Applied Mathematics (with demonstrable training / experience in nonlinear dynamics / nonlinear differential equations, Computing Science (with demonstrable training / experience in AI / ML / ANN coding).

Application Procedure:

Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php.

You should apply for PhD in Engineering to ensure your application is passed to the correct team for processing.

Please clearly note the name of the lead supervisor and project title on the application form. If you do not include these details, it may not be considered for the studentship.

Your application must include: A personal statement, an up-to-date copy of your academic CV, and clear copies of your educational certificates and transcripts.

Please note: you do not need to provide a research proposal with this application.

Informal enquiries can be made by contacting Professor S Aphale at s.aphale@abdn.ac.uk. If you require any additional assistance in submitting your application or have any queries about the application process, please don't hesitate to contact us at researchadmissions@abdn.ac.uk