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We have 87 Artificial Intelligence (control) PhD Projects, Programmes & Scholarships

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Artificial Intelligence (control) PhD Projects, Programmes & Scholarships

We have 87 Artificial Intelligence (control) PhD Projects, Programmes & Scholarships

Model Predictive Control for Autonomous Vehicles and Robots [SELF-FUNDED STUDENTS ONLY]

  Research Group: Visual Computing
Model predictive control (MPC) is a family of modern control methods that have demonstrated impressive performance in a variety of scenarios, including in robotics and autonomous vehicle control. Read more

Model Predictive Control for Autonomous Vehicles and Robots

  Research Group: Visual Computing
Model predictive control (MPC) is a family of modern control methods that have demonstrated impressive performance in a variety of scenarios, including in robotics and autonomous vehicle control. Read more

Model Predictive Control for Autonomous Vehicles and Robots [Self Funded Students Only]

Model predictive control (MPC) is a family of modern control methods that have demonstrated impressive performance in a variety of scenarios, including in robotics and autonomous vehicle control. Such methods rely on models that can predict a system's future behaviour in response to control inputs in order to find the optimal actions that drive the system to a desired state. Read more

Nonlinear Model Predictive Control

Optimization-based control explores the use of optimization algorithms for feedback control of dynamical systems. For example, model predictive control (MPC) is a widely used optimization-based control method, allowing systematic and optimal handling of constraints, nonlinearities and uncertainties. Read more

Learning for Control: Enabling Efficient Networked Autonomous Systems

Supervisory Team: Konstantinos Gatsis . Project description. There is an ongoing transformation in engineering autonomous systems that aim to achieve complex objectives with limited human intervention in applications such as robotics, self-driving cars, and industrial systems. Read more

Distributed active reinforcement learning for multi-agent planning and control

With the rapid development of network-connected systems, coordination and cooperation among the subsystems/agents have become increasingly important and powerful in many control and robotics applications. Read more

Phased array fibre lasers with machine learning

Supervisory Team: Prof Johan Nilsson, Dr William Kerridge-Johns. Project description. This project combines state of the art optical fibre laser amplifiers with machine learning control to produce next-generation lasers. Read more

Bio-Inspired Models and Biologically Plausible Mechanisms for Long-Term Motion Learning

Biological systems can learn from interactions with their environment throughout their lifetime. Learning is a defining ability of biological systems, whereby experience leads to behavioral adaptations that improve performance. Read more

PhD in Thermal route optimization of predictive controls to improve BEV efficiency using AI & ML

Route information has significantly improved the optimization of hybrid vehicle propulsion by determining the most efficient power source for different parts of a journey. Read more

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