29 citations · 160 across the 58 of their papers we have counts for
17 papers · 1 filter
Model Predictive Control with Multiple Constraint Horizons
Allan Andre do Nascimento, Han Wang, Antonis Papachristodoulou +1
We propose a Model Predictive Control (MPC) formulation for nonlinear systems without terminal penalty or dedicated stabilizing terminal set, in which state constraints are enforce…
Distributed equilibrium seeking in aggregative games: linear convergence under singular perturbations lens
Guido Carnevale, Filippo Fabiani, Filiberto Fele +2
We present a fully-distributed algorithm for Nash equilibrium seeking in aggregative games over networks. The proposed scheme endows each agent with a gradient-based scheme equippe…
Constraint Horizon in Model Predictive Control
Allan Andre Do Nascimento, Han Wang, Antonis Papachristodoulou +1
In this work, we propose a Model Predictive Control (MPC) formulation incorporating two distinct horizons: a prediction horizon and a constraint horizon. This approach enables a de…
Continuous-time Data-driven Barrier Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We consider the problem of verifying safety for continuous-time dynamical systems. Developing upon recent advancements in data-driven verification, we use only a finite number of s…
Data-Driven Certificate Synthesis
Luke Rickard, Alessandro Abate, Kostas Margellos
We investigate the problem of verifying different properties of discrete time dynamical systems, namely, reachability, safety and reach-while-avoid. To achieve this, we adopt a dat…
Probabilistically safe controllers based on control barrier functions and scenario model predictive control
Allan Andre do Nascimento, Antonis Papachristodoulou, Kostas Margellos
Control barrier functions (CBFs) offer an efficient framework for designing real-time safe controllers. However, CBF-based controllers can be short-sighted, resulting in poor perfo…
Safe and Stable Filter Design Using a Relaxed Compatibitlity Control Barrier -- Lyapunov Condition
Han Wang, Kostas Margellos, Antonis Papachristodoulou
In this paper, we propose a quadratic programming-based filter for safe and stable controller design, via a Control Barrier Function (CBF) and a Control Lyapunov Function (CLF). Ou…
Learning Robust Policies for Uncertain Parametric Markov Decision Processes
Luke Rickard, Alessandro Abate, Kostas Margellos
Synthesising verifiably correct controllers for dynamical systems is crucial for safety-critical problems. To achieve this, it is important to account for uncertainty in a robust m…
Distributed Safe Control Design and Probabilistic Safety Verification for Multi-Agent Systems
Han Wang, Antonis Papachristodoulou, Kostas Margellos
We propose distributed iterative algorithms for safe control design and safety verification for networked multi-agent systems. These algorithms rely on distributing a control barri…
Multi-objective low-thrust spacecraft trajectory design using reachability analysis
Nikolaus Vertovec, Sina Ober-Blöbaum, Kostas Margellos
One of the fundamental problems in spacecraft trajectory design is finding the optimal transfer trajectory that minimizes the propellant consumption and transfer time simultaneousl…
Safety-Aware Hybrid Control of Airborne Wind Energy Systems
Nikolaus Vertovec, Sina Ober-Blöbaum, Kostas Margellos
A fundamental concern in progressing Airborne Wind Energy (AWE) operations towards commercial success, is guaranteeing that safety requirements placed on the systems are met. Due t…
Tracking-based distributed equilibrium seeking for aggregative games
Guido Carnevale, Filippo Fabiani, Filiberto Fele +2
We propose fully-distributed algorithms for Nash equilibrium seeking in aggregative games over networks. We first consider the case where local constraints are present and we desig…
Safety-Aware Optimal Control for Motion Planning with Low Computing Complexity
Xuda Ding, Han Wang, Jianping He +3
The existence of multiple irregular obstacles in the environment introduces nonconvex constraints into the optimization for motion planning, which makes the optimal control problem…
Verification of safety critical control policies using kernel methods
Nikolaus Vertovec, Sina Ober-Blöbaum, Kostas Margellos
Hamilton-Jacobi reachability methods for safety-critical control have been well studied, but the safety guarantees derived rely on the accuracy of the numerical computation. Thus,…
An incremental scenario approach for building energy management with uncertain occupancy
Arman Karshenas, Kostas Margellos, Simone Garatti
We deal with the problem of energy management in buildings subject to uncertain occupancy. To this end, we formulate this as a finite horizon optimization program and optimize with…
On the connection between compression learning and scenario based optimization
Kostas Margellos, Maria Prandini, John Lygeros
We investigate the connections between compression learning and scenario based optimization. We first show how to strengthen, or relax the consistency assumption at the basis of co…
A scenario approach for non-convex control design
Sergio Grammatico, Xiaojing Zhang, Kostas Margellos +2
Randomized optimization is an established tool for control design with modulated robustness. While for uncertain convex programs there exist randomized approaches with efficient sa…