22 citations · 43 across the 10 of their papers we have counts for
11 papers
Safe Reinforcement Learning with Minimal Supervision
Alexander Quessy, Thomas Richardson, Sebastian East
Reinforcement learning (RL) in the real world necessitates the development of procedures that enable agents to explore without causing harm to themselves or others. The most succes…
Differentiable Predictive Control for Robotics: A Data-Driven Predictive Safety Filter Approach
John Viljoen, Wenceslao Shaw Cortez, Jan Drgona +3
Model Predictive Control (MPC) is effective at generating safe control strategies in constrained scenarios, at the cost of computational complexity. This is especially the case in…
Imitation Learning of Stabilizing Policies for Nonlinear Systems
Sebastian East
There has been a recent interest in imitation learning methods that are guaranteed to produce a stabilizing control law with respect to a known system. Work in this area has genera…
Scenario Model Predictive Control for Data-based Energy Management in Plug-in Hybrid Electric Vehicles
Sebastian East, Mark Cannon
One of the major limitations of optimization-based strategies for allocating the power flow in hybrid powertrains is that they rely on predictions of future power demand. These pre…
Optimal Power Allocation in Battery/Supercapacitor Electric Vehicles using Convex Optimization
Sebastian East, Mark Cannon
This paper presents a framework for optimizing the power allocation between a battery and supercapacitor in an electric vehicle energy storage system. A convex optimal control form…
Infinite-Horizon Differentiable Model Predictive Control
Sebastian East, Marco Gallieri, Jonathan Masci +2
This paper proposes a differentiable linear quadratic Model Predictive Control (MPC) framework for safe imitation learning. The infinite-horizon cost is enforced using a terminal c…
Fast Optimal Energy Management with Engine On/Off Decisions for Plug-in Hybrid Electric Vehicles
Sebastian East, Mark Cannon
In this paper we demonstrate a novel alternating direction method of multipliers (ADMM) algorithm for the solution of the hybrid vehicle energy management problem considering both…
Parallel ADMM for robust quadratic optimal resource allocation problems
Zawar Qureshi, Sebastian East, Mark Cannon
An alternating direction method of multipliers (ADMM) solver is described for optimal resource allocation problems with separable convex quadratic costs and constraints and linear…
Energy Management in Plug-in Hybrid Electric Vehicles: Convex Optimization Algorithms for Model Predictive Control
Sebastian East, Mark Cannon
This paper details an investigation into the computational performance of algorithms used for solving a convex formulation of the optimization problem associated with model predict…
An ADMM Algorithm for MPC-based Energy Management in Hybrid Electric Vehicles with Nonlinear Losses
Sebastian East, Mark Cannon
In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for energy management in hybrid electric vehicles, and an Alternating Direction Met…
ADMM for MPC with state and input constraints, and input nonlinearity
Sebastian East, Mark Cannon
In this paper we propose an Alternating Direction Method of Multipliers (ADMM) algorithm for solving a Model Predictive Control (MPC) optimization problem, in which the system has…