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Feedback optimisation is an emerging technique aiming at steering a system to an optimal steady state for a given objective function. We show that it is possible to employ this control strategy in a distributed manner. Moreover, we prove…

Optimization and Control · Mathematics 2022-03-01 Antonio Terpin , Sylvain Fricker , Michel Perez , Mathias Hudoba de Badyn , Florian Dörfler

State-dependent networked dynamical systems are ones where the interconnections between agents change as a function of the states of the agents. Such systems are highly nonlinear, and a cohesive strategy for their control is lacking in the…

Optimization and Control · Mathematics 2018-09-21 Mathias Hudoba de Badyn , Utku Eren , Behcet Acikmese , Mehran Mesbahi

This article shows how the recent breakthroughs in Reinforcement Learning (RL) that have enabled robots to learn to play arcade video games, walk or assemble colored bricks, can be used to perform other tasks that are currently at the core…

Artificial Intelligence · Computer Science 2017-02-01 Francois Belletti , Daniel Haziza , Gabriel Gomes , Alexandre M. Bayen

We establish a separation principle for the output feedback stabilisation of state-affine systems that are observable at the stabilization target. Relying on control templates (recently introduced in [4]), that allow to approximate a…

Optimization and Control · Mathematics 2024-11-15 Ludovic Sacchelli , Lucas Brivadis , Ulysse Serres , Itaï Ben Yaacov

In a parallel discrete-event simulation (PDES) scheme, tasks are distributed among processing elements (PEs), whose progress is controlled by a synchronization scheme. For lattice systems with short-range interactions, the progress of the…

Statistical Mechanics · Physics 2007-05-23 G. Korniss , M. A. Novotny , H. Guclu , Z. Toroczkai , P. A. Rikvold

Rapid performance recovery from unforeseen environmental perturbations remains a grand challenge in swarm robotics. To solve this challenge, we investigate a behaviour adaptation approach, where one searches an archive of controllers for…

Robotics · Computer Science 2024-01-08 David M. Bossens , Danesh Tarapore

In this paper, we aim to design and analyze distributed Bayesian estimation algorithms for sensor networks. The challenges we address are to (i) derive a distributed provably-correct algorithm in the functional space of probability…

Machine Learning · Computer Science 2025-03-25 Parth Paritosh , Nikolay Atanasov , Sonia Martinez

We study feedback stabilization of continuous-time linear systems under finite data-rate constraints in the presence of unknown disturbances. A communication and control strategy based on sampled and quantized state measurements is…

Systems and Control · Electrical Eng. & Systems 2026-03-31 Mahmoud Zamani , Guosong Yang

Populations do not only interact over time but also age over time. It is therefore common to model them as age-structured PDEs, where age is the space variable. Since the models also involve integrals over age, both in the birth process and…

Systems and Control · Electrical Eng. & Systems 2026-02-17 Carina Veil , Miroslav Krstić , Iasson Karafyllis , Mamadou Diagne , Oliver Sawodny

Deviations of grid frequency from the nominal frequency are an indicator of the global imbalance between genera- tion and load. Two types of control, a distributed propor- tional control and a centralized integral control, are cur- rently…

Systems and Control · Computer Science 2012-11-20 Krishnamurthy Dvijotham , Michael Chertkov , Scott Backhaus

Automated model discovery of partial differential equations (PDEs) usually considers a single experiment or dataset to infer the underlying governing equations. In practice, experiments have inherent natural variability in parameters,…

Machine Learning · Statistics 2021-11-25 Georges Tod , Gert-Jan Both , Remy Kusters

In this paper the problem of driving the state of a network of identical agents, modeled by boundary-controlled heat equations, towards a common steady-state profile is addressed. Decentralized consensus protocols are proposed to address…

Systems and Control · Computer Science 2015-09-24 A. Pilloni , A. Pisano , Y. Orlov , E. Usai

This paper presents a scalable Bayesian technique for decentralized state estimation from multiple platforms in dynamic environments. As has long been recognized, centralized architectures impose severe scaling limitations for distributed…

Artificial Intelligence · Computer Science 2012-12-12 Matthew Rosencrantz , Geoffrey Gordon , Sebastian Thrun

In this paper, we design a controller for an interconnected system consisting of a linear Stochastic Differential Equation (SDE) actuated through a linear hyperbolic Partial Differential Equation (PDE). Our approach aims to minimize the…

Optimization and Control · Mathematics 2024-05-15 Gabriel Velho , Jean Auriol , Riccardo Bonalli , Islam Boussaada

In this paper, we study the controllability and stabilizability properties of the Kolmogorov forward equation of a continuous time Markov chain (CTMC) evolving on a finite state space, using the transition rates as the control parameters.…

Systems and Control · Computer Science 2017-03-29 Karthik Elamvazhuthi , Vaibhav Deshmukh , Matthias Kawski , Spring Berman

Inspired and underpinned by the idea of integral feedback, a distributed constant gain algorithm is proposed for multi-agent networks to solve convex optimization problems with local linear constraints. Assuming agent interactions are…

Optimization and Control · Mathematics 2021-11-19 Xuan Wang , Shaoshuai Mou , Brian. D. O. Anderson

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid…

Systems and Control · Electrical Eng. & Systems 2024-10-22 Adam Lechowicz , Joshua Comden , Andrey Bernstein

Data-driven discovery of partial differential equations (PDEs) has attracted increasing attention in recent years. Although significant progress has been made, certain unresolved issues remain. For example, for PDEs with high-order…

Machine Learning · Computer Science 2021-09-14 Hao Xu , Dongxiao Zhang , Nanzhe Wang

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the…

Optimization and Control · Mathematics 2018-01-09 Randa Herzallah

In micro-assembly applications, ensemble of chiplets immersed in a dielectric fluid are steered using dielectrophoretic forces induced by an array of electrode population. Generalizing the finite population deterministic models proposed in…

Dynamical Systems · Mathematics 2023-05-17 Iman Nodozi , Abhishek Halder , Ion Matei