Dr Morgan Jones
School of Electrical and Electronic Engineering
Lecturer in Machine Learning and Control Theory
morgan.jones@sheffield.ac.uk
Amy Johnson Building
Full contact details
Dr Morgan Jones
School of Electrical and Electronic Engineering
Amy Johnson Building
Portobello Street
Sheffield
S1 3JD
School of Electrical and Electronic Engineering
Amy Johnson Building
Portobello Street
Sheffield
S1 3JD
- Profile
-
Morgan Jones received the B.S. and Mmath in Mathematics from The University of Oxford, England in 2016. He received his PhD in Aerospace Engineering from Arizona State University (ASU), USA in 2021. Currently, he is a lecturer in Machine Learning and Control Theory at the University of Sheffield, UK.
At Arizona State University Morgan was a member of Cybernetic Systems and Controls Laboratory (CSCL) from 2016 till 2021.
- Research interests
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- Dynamic programming, reinforcement learning, battery scheduling, path planning and obstacle avoidance
- Optimal control: Developing convex optimization tools to solve the Hamilton Jacobi Bellman (HJB) PDE
- Nonlinear systems analysis: Approximating regions of attraction, maximal invariant sets, reachable sets and attractor sets
- Sum-of-Squares (SOS) programming
- Publications
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Journal articles
- Model predictive bang-bang controller synthesis via approximate value functions. IFAC-PapersOnLine, 58(17), 127-132. View this article in WRRO
- Sublevel Set Approximation in the Hausdorff and Volume Metric With Application to Path Planning and Obstacle Avoidance. IEEE Transactions on Automatic Control, 69(11), 8112-8119.
Conference proceedings
- Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI). 2024 American Control Conference (ACC) (pp 2879-2884), 10 July 2024 - 12 July 2024.
- Existence of Partially Quadratic Lyapunov Functions That Can Certify The Local Asymptotic Stability of Nonlinear Systems. 2023 American Control Conference (ACC) (pp 4130-4135), 31 May 2023 - 2 June 2023.
- Excitation Optimization for Estimating Battery Health Parameters using Reinforcement Learning considering Information Content and Bias. 2023 American Control Conference (ACC) (pp 3093-3098), 31 May 2023 - 2 June 2023.
Preprints
- Feedback Linearisation with State Constraints.
- Bounding the Error of Value Functions in Sobolev Norm Yields Bounds on
Suboptimality of Controller Performance.
- Approximate Projections onto the Positive Semidefinite Cone Using
Randomization.
- Model Predictive Bang-Bang Controller Synthesis via Approximate Value
Functions.
- Learning Polynomial Representations of Physical Objects with Application
to Certifying Correct Packing Configurations.
- Model predictive bang-bang controller synthesis via approximate value functions. IFAC-PapersOnLine, 58(17), 127-132. View this article in WRRO
- Teaching activities
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- ACS234 Systems Engineering Mathematics II