63 citations · 220 across the 13 of their papers we have counts for
13 papers
A Sequential Deep Learning Algorithm for Sampled Mixed-integer Optimisation Problems
Mohammadreza Chamanbaz, Roland Bouffanais
Mixed-integer optimisation problems can be computationally challenging. Here, we introduce and analyse two efficient algorithms with a specific sequential design that are aimed at…
A Physics-Based Attack Detection Technique in Cyber-Physical Systems: A Model Predictive Control Co-Design Approach
Mohammadreza Chamanbaz, Fabrizio Dabbene, Roland Bouffanais
In this paper a novel approach to co-design controller and attack detector for nonlinear cyber-physical systems affected by false data injection (FDI) attack is proposed. We augmen…
Robust Stabilization of Resource Limited Networked Control Systems Under Denial-of-Service Attack
Niladri Sekhar Tripathy, Mohammadreza Chamanbaz, Roland Bouffanais
In this paper, we consider a class of denial-of-service (DoS) attacks, which aims at overloading the communication channel. On top of the security issue, continuous or periodic tra…
Randomized Constraints Consensus for Distributed Robust Mixed-Integer Programming
Mohammadreza Chamanbaz, Giuseppe Notarstefano, Francesco Sasso +1
In this paper, we consider a network of processors aiming at cooperatively solving mixed-integer convex programs subject to uncertainty. Each node only knows a common cost function…
Algorithms for Optimal AC Power Flow in the Presence of Renewable Sources
Mohammadreza Chamanbaz, Fabrizio Dabbene, Constantino Lagoa
This chapter presents recent solutions to the optimal power flow (OPF) problem in the presence of renewable energy sources (RES), {such} as solar photo-voltaic and wind generation.…
Optimal Network Topology for Effective Collective Response
David Mateo, Nikolaj Horsevad, Vahid Hassani +2
Natural, social, and artificial multi-agent systems usually operate in dynamic environments, where the ability to respond to changing circumstances is a crucial feature. An effecti…
Randomized Constraints Consensus for Distributed Robust Linear Programming
Mohammadreza Chamanbaz, Giuseppe Notarstefano, Roland Bouffanais
In this paper we consider a network of processors aiming at cooperatively solving linear programming problems subject to uncertainty. Each node only knows a common cost function an…
Adapting Low-Cost Platforms for Robotics Research
Thommen George Karimpanal, Mohammadreza Chamanbaz, Wenzheng Li +3
Validation of robotics theory on real-world hardware platforms is important to prove the practical feasibility of algorithms. This paper discusses some of the lessons learned while…
Swarm-Enabling Technology for Multi-Robot Systems
Mohammadreza Chamanbaz, David Mateo, Brandon M. Zoss +4
Swarm robotics has experienced a rapid expansion in recent years, primarily fueled by specialized multi-robot systems developed to achieve dedicated collective actions. These speci…
AC optimal power flow in the presence of renewable sources and uncertain loads
Mohammadreza Chamanbaz, Fabrizio Dabbene, Constantino Lagoa
The increasing penetration of renewable energy resources, paired with the fact that load can vary significantly, introduce a high degree of uncertainty in the behavior of modern po…
Randomized and robust methods for uncertain systems using R-RoMulOC, with applications to DEMETER satellite benchmark
Mohammadreza Chamanbaz, Fabrizio Dabbene, Dimitri Peaucelle +2
R-RoMulOC is a freely distributed toolbox which aims at making easily available to the users different optimization-based methods for dealing with uncertain systems. It implements…
A Statistical Learning Theory Approach for Uncertain Linear and Bilinear Matrix Inequalities
Mohammadreza Chamanbaz, Fabrizio Dabbene, Roberto Tempo +2
In this paper, we consider the problem of minimizing a linear functional subject to uncertain linear and bilinear matrix inequalities, which depend in a possibly nonlinear way on a…
Sequential Randomized Algorithms for Convex Optimization in the Presence of Uncertainty
Mohammadreza Chamanbaz, Fabrizio Dabbene, Roberto Tempo +2
In this paper, we propose new sequential randomized algorithms for convex optimization problems in the presence of uncertainty. A rigorous analysis of the theoretical properties of…