Dr Morgan Jones
School of Electrical and Electronic Engineering
Lecturer in Machine Learning and Control Theory
morgan.jones@sheffield.ac.uk
+44 114 222 5139
+44 114 222 5139
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
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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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Details of my research area:
- 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
- Sublevel Set Approximation in the Hausdorff and Volume Metric With Application to Path Planning and Obstacle Avoidance. IEEE Transactions on Automatic Control, 1-8.
- A converse sum of squares lyapunov function for outer approximation of minimal attractor sets of nonlinear systems. Journal of Computational Dynamics, 10(1), 48-74.
- Combining Trajectory Data with Analytical Lyapunov Functions for Improved Region of Attraction Estimation. IEEE Control Systems Letters, 1-1.
- A generalization of Bellman's equation with application to path planning, obstacle avoidance and invariant set estimation. Automatica, 127.
- Extensions of the dynamic programming framework: Battery scheduling, demand charges, and renewable integration. IEEE Transactions on Automatic Control, 66(4), 1602-1617.
Conference proceedings papers
- Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI). 2024 American Control Conference (ACC), Vol. 49 (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), 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), 31 May 2023 - 2 June 2023.
- A Converse Sum of Squares Lyapunov Function for Outer Approximation of Minimal Attractor Sets of Nonlinear Systems
- Converse Lyapunov Functions and Converging Inner Approximations to Maximal Regions of Attraction of Nonlinear Systems. Proceedings of the IEEE Conference on Decision and Control, Vol. 2021-December (pp 5312-5319)
- Relaxing the Hamilton Jacobi Bellman Equation to Construct Inner and Outer Bounds on Reachable Sets. Proceedings of the IEEE Conference on Decision and Control, Vol. 2019-December (pp 2397-2404)
- Using SOS and sublevel set volume minimization for estimation of forward reachable sets. IFAC-PapersOnLine, Vol. 52(16) (pp 484-489)
- Using SOS for optimal semialgebraic representation of sets: Finding minimal representations of limit cycles, chaotic attractors and unions. Proceedings of the American Control Conference, Vol. 2019-July (pp 2084-2091)
- Solving dynamic programming with supremum terms in the objective and application to optimal battery scheduling for electricity consumers subject to demand charges. 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, Vol. 2018-January (pp 1323-1329)
- Estimating the region of attraction using polynomial optimization: A converse Lyapunov result. 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, Vol. 2018-January (pp 1796-1802)
Preprints
- Model Predictive Bang-Bang Controller Synthesis via Approximate Value Functions.
- Learning Polynomial Representations of Physical Objects with Application to Certifying Correct Packing Configurations.
- Sublevel Set Approximation in The Hausdorff and Volume Metric with Application to Path Planning and Obstacle Avoidance.
- Existence of Partially Quadratic Lyapunov Functions That Can Certify The Local Asymptotic Stability of Nonlinear Systems.
- Combining Trajectory Data with Analytical Lyapunov Functions for Improved Region of Attraction Estimation.
- Converse Lyapunov Functions and Converging Inner Approximations to Maximal Regions of Attraction of Nonlinear Systems.
- Polynomial Approximation of Value Functions and Nonlinear Controller Design with Performance Bounds.
- A Generalization of Bellman's Equation with Application to Path Planning, Obstacle Avoidance and Invariant Set Estimation.
- Relaxing The Hamilton Jacobi Bellman Equation To Construct Inner And Outer Bounds On Reachable Sets.
- Using SOS and Sublevel Set Volume Minimization for Estimation of Forward Reachable Sets.
- Extensions of the Dynamic Programming Framework: Battery Scheduling, Demand Charges, and Renewable Integration.
- Using SOS for Optimal Semialgebraic Representation of Sets: Finding Minimal Representations of Limit Cycles, Chaotic Attractors and Unions.
- A Dynamic Programming Approach to Evaluating Multivariate Gaussian Probabilities.
- Solving Dynamic Programming with Supremum Terms in the Objective and Application to Optimal Battery Scheduling for Electricity Consumers Subject to Demand Charges.
- Teaching interests
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2022: ACS234 Systems Engineering Mathematics II