Article
Computer Science, Artificial Intelligence
Ran Yi, Zipeng Ye, Wang Zhao, Minjing Yu, Yu-Kun Lai, Yong-Jin Liu
Summary: In this paper, we propose a method to compute feature-aware CSS in videos by inducing a uniform tessellation on the video manifold, which results in supervoxels that align well with local video boundaries.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2021)
Article
Mathematics, Applied
Ivan Gonzalez, Rustum Choksi, Jean-Christophe Nave
Summary: This study presents a simple deterministic method for finding optimal centroidal Voronoi tessellations in a two-dimensional domain. The method is based on generators moving away from the closest neighbor by a certain distance to access low energy CVTs. Statistical analysis shows the hybrid method performs well compared to traditional methods and quasi-Newton methods.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Biotechnology & Applied Microbiology
Xuan Guo, Yuepeng Chen, Dongming Zhao, Guangyu Luo
Summary: This paper proposes a coverage control optimization algorithm based on a biological competition mechanism to effectively solve the static area coverage problem of a heterogeneous group of autonomous underwater vehicles (AUVs).
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Ali Mirani, Kovendhan Vijayan, Shen Li, Zonglong He, Erik Agrell, Jochen Schroder, Peter Andrekson, Magnus Karlsson
Summary: In this article, a low-complexity geometric shaping method based on multidimensional lattices is investigated both in experiments and simulations. The modulation formats designed based on this method are called Voronoi constellations (VCs) and we study them in 8, 16, and 32 dimensions. We obtain transmission reach improvements of up to 22% and 70% for VCs compared to 4 QAM and 16 QAM, respectively, in nonlinear long-haul fiber transmission. Furthermore, the mutual information and generalized mutual information are estimated and compared to QAM formats at the same spectral efficiencies.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Jiajun Chai, Yuanheng Zhu, Dongbin Zhao
Summary: In this work, a novel method called neighboring variational information flow (NVIF) is proposed to enhance communication among neighboring agents and address the limitations of existing methods in large-scale multiagent systems. A two-stage training mechanism is introduced to stabilize the training process, and theoretical analysis and experiment results demonstrate the superiority and potential of the proposed method.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Cong Wang, Shengyuan Xu, Deming Yuan, Yuming Chu, Zhengqiang Zhang
Summary: This paper addresses distributed convex optimization problems for multi-agent systems using the push-sum distributed dual averaging algorithm, while considering subgradient delays. The main result proves that the algorithm converges with sublinear growth of error, and a numerical example is provided to demonstrate its performance.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Computer Science, Theory & Methods
Guoqing Wu, Hongyun Tian, Guo Lu, Wei Wang
Summary: This paper proposes a scalable parallel algorithm for constructing 3D Voronoi tessellations. The algorithm evenly distributes input particles between blocks using kd-tree decomposition to construct the correct global Voronoi topology. Experimental results demonstrate the high efficiency of the algorithm on large datasets.
PARALLEL COMPUTING
(2023)
Article
Automation & Control Systems
Naoki Hayashi, Kazunori Sakurama
Summary: This study introduces a cooperative car-sharing system where different service providers operate a sharing service together. A distributed algorithm is proposed for rebalancing control to minimize the number of empty vehicles, taking into account dispatchable vehicles and parking availability at car stations. Providers cooperatively search for an optimal solution by sharing estimated values of the optimal dual solutions through communication networks. Event-driven communication is considered, triggering information exchange with neighboring providers only when the change in the estimated optimal dual solution exceeds a threshold. Numerical examples demonstrate that the estimations of all service providers meet the optimal rebalancing solutions.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Martin Baehr, Johannes Buhl, Georg Radow, Johannes Schmidt, Markus Bambach, Michael Breuss, Armin Fuegenschuh
Summary: This study focuses on two mathematical problems related to the layer-wise production process of a workpiece. The first problem involves automatically constructing a honeycomb structure using Lloyd's algorithm and Voronoi tessellation. The second problem is to find an optimal tool path through mixed-integer linear programming to ensure minimal production time and high quality of the workpiece.
OPTIMIZATION AND ENGINEERING
(2021)
Article
Engineering, Mechanical
Samane Kaviri, Ahmadreza Tahsiri, Hamid D. Taghirad
Summary: The paper proposes a cooperative deployment framework for UAVs to clean up oil spills, utilizing Gaussian mixture models and Voronoi tessellation for optimal location determination, along with a spraying adjustment strategy for more effective dispersal of oil spills.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2021)
Article
Telecommunications
Jiangtao Li, Xu Bao, Wence Zhang
Summary: This study investigates the optimal configuration of LEDs in indoor environments under the constraints of illumination and quality of experience (QoE), using Voronoi tessellation (VT) and centroidal Voronoi tessellation (CVT) theory combined with the Lloyd's algorithm. Simulation results demonstrate that the proposed deployment approach can provide better QoE performance with fewer LEDs under the same conditions.
CHINA COMMUNICATIONS
(2021)
Article
Automation & Control Systems
Bhagyashri Telsang, Seedik M. Djouadi
Summary: This article presents a method for computing centroidal Voronoi tessellations in higher dimensional spaces, and proves that such tessellations can be efficiently computed under certain conditions. Numerical evaluations and comparisons with other methods validate the feasibility and efficiency of the proposed method.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Physics, Mathematical
David P. Bourne, Riccardo Cristoferi
Summary: The study proves an asymptotic crystallization result in two dimensions for a class of nonlocal particle systems, focusing on best approximation of probability measures with unknown particle properties. It explores a one-parameter family of constraints and applications in various fields. Results show the asymptotic optimality of a triangular lattice for constrained best approximation and extend previous crystallization findings to a broader class of systems.
COMMUNICATIONS IN MATHEMATICAL PHYSICS
(2021)
Article
Mathematics, Applied
Claudio Contardo, Alain Hertz
Summary: The paper introduces an algorithm to find the minimum number of disks needed to cover a given region by alternating between solving a set-cover problem and constructing a Laguerre-Voronoi diagram of circle set. Experimental results demonstrate the effectiveness of the proposed algorithm, especially when a small number of disks are required to cover the region.
DISCRETE APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Cheng-Cheng Yang, Teng-Hu Cheng
Summary: This article presents a leader-follower system for cooperatively swinging a payload without interagent communication. The leader actively swings the payload while the follower compensates for angle difference and mimics the leader's swing. Unscented Kalman filters are used to estimate external forces, eliminating the need for force sensors. Stability analysis and simulation demonstrate the stability and performance of the system.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Kevin D. Smith, Saber Jafarpour, Francesco Bullo
Summary: This article analyzes the transient stability of droop-controlled inverter networks subject to multiple operating constraints and provides two sets of criteria for achieving frequency synchronization in postfault trajectories. By incorporating information from loop flows, less-conservative transient stability conditions are obtained, and the robustness of the network to parameter disturbances is quantified.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Kevin D. D. Smith, Francesco Bullo
Summary: Strongly contracting dynamical systems and their adjoint systems are shown to have the same rate of contraction under time reversal. This duality leads to new convergence conditions for the Method of Successive Approximations (MSA) algorithm and establishes uniqueness of the optimal control and sufficiency of Pontryagin's minimum principle under certain assumptions.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Elizabeth Y. Huang, Dario Paccagnan, Wenjun Mei, Francesco Bullo
Summary: Tackling complex team problems requires understanding each team member's skills in order to devise a task assignment maximizing the team performance. This article proposes a novel quantitative model describing the decentralized process by which individuals in a team learn who has what abilities, while concurrently assigning tasks to each of the team members. We show that the appraisal states can be reduced to a lower dimension due to the presence of conserved quantities associated with the cycles of the appraisal network. Building on this, we provide rigorous results characterizing the ability, or inability, of the team to learn each other's skills and, thus, converge to an allocation maximizing the team performance. We complement our analysis with extensive numerical experiments.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Marco Coraggio, Saber Jafarpour, Francesco Bullo, Mario di Bernardo
Summary: Given a flow network with variable suppliers and fixed consumers, the minimax flow problem aims to minimize the maximum flow between nodes, subject to flow conservation and capacity constraints. In this study, we address this problem in a distributed manner by introducing the concept of consensus problem between the maximum downstream flows. Additionally, we propose a distributed algorithm to estimate these quantities. Finally, we apply these theoretical results to design an online distributed controller for preventing overcurrent in microgrids.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Automation & Control Systems
Pedro Cisneros-Velarde, Francesco Bullo
Summary: In this article, a distributed algorithm is proposed for computing the Wasserstein barycenter of the initial measures in a multiagent system. The algorithm is based on stochastic, asynchronous, and pairwise exchange of information, and displacement interpolation in the Wasserstein space. The evolution of the algorithm is characterized and it is proven to compute the Wasserstein barycenter under various conditions. Two versions of the algorithm are introduced, one for computing a standard Wasserstein barycenter and the other for computing a randomized Wasserstein barycenter. The algorithm is further specialized to Gaussian distributions and its connection to opinion dynamics is explored.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Automation & Control Systems
Saber Jafarpour, Alexander Davydov, Francesco Bullo
Summary: In this paper, we investigate the contractivity of monotone systems and the exponential convergence of positive systems using non-Euclidean norms. We introduce the concept of conic matrix measure as a framework to study stability of monotone and positive systems, and study its properties and its connection with weak pairings and standard matrix measures. By using conic matrix measures and weak pairings, we characterize the contractivity and incremental stability of monotone systems with respect to non-Euclidean norms. Moreover, we provide sufficient conditions for the exponential convergence of positive systems to their equilibria using conic matrix measures. We present novel results on the contractivity of excitatory Hopfield neural networks and the stability of interconnected systems using nonmonotone positive comparison systems.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Wenjie Liu, Jian Sun, Gang Wang, Francesco Bullo, Jie Chen
Summary: This article presents a data-driven model predictive control scheme for resilient control of linear time-invariant systems under denial-of-service attacks, achieving similar resilience as model-based control methods.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Anton V. Proskurnikov, Alexander Davydov, Francesco Bullo
Summary: This paper presents a novel nonpolynomial S-Lemma that provides constructive criteria for the existence of functions defined by weighted lp norms in the absolute stability of Lur'e-type systems. It introduces new absolute stability and absolute contractivity criteria, including a simple proof of the Aizerman and Kalman conjectures for positive Lur'e systems.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2023)
Article
Automation & Control Systems
Chiara Ravazzi, Francesco Bullo, Fabrizio Dabbene
Summary: This article explores how individuals' opinions evolve in modern society through continuous interactions and interpersonal influences. It proposes a mathematical model to study oligarchic influence systems and presents a data-driven approach to estimate social power.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Automation & Control Systems
Gilberto Diaz-Garcia, Francesco Bullo, Jason R. Marden
Summary: Markov chains are increasingly being used for persistent robotic surveillance. The motivations for this choice are easy implementation, unpredictable surveillance patterns, and well-studied mathematics. However, applying previous results to scenarios with multiple agents can lead to intractable algorithms due to increased dimensionality.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Kevin D. Smith, Francesco Bullo
Summary: The basic reproduction number R0, which represents the typical number of secondary infections arising from a single infected individual, is characterized in this note by stability and geometric program descriptions. The geometric program characterization enables the transformation of R0-constrained and budget-constrained optimal resource allocation problems into convex optimization problems, allowing for efficient allocation of vaccines and antidotes. By targeting R0 instead of the spectral abscissa of the Jacobian matrix, different and potentially more effective solutions can be obtained.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Veronica Centorrino, Anand Gokhale, Alexander Davydov, Giovanni Russo, Francesco Bullo
Summary: This letter investigates the stability conditions of continuous-time Hopfield and firing-rate neural networks using contraction theory. It presents useful algebraic results on matrix polytopes and products of symmetric matrices. Sufficient conditions for strong and weak Euclidean contractivity of both models with symmetric weights and non-smooth activation functions are given. The contraction analysis leads to log-optimal contraction rates in almost all symmetric synaptic matrices. Finally, a firing-rate neural network model is proposed to solve a quadratic optimization problem with box constraints.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Robin Delabays, Francesco Bullo
Summary: This letter studies the celebrated Kuramoto-Sakaguchi model of coupled oscillators using two recent concepts, namely appropriately-defined subsets of the $n$-torus called winding cells and the semicontractivity of the model. The letter establishes the local semicontractivity of the Kuramoto-Sakaguchi model and characterizes the multistability of the model by proving the at most uniqueness of synchronous states within convex phase-cohesive subsets of winding cells. The sufficient conditions and estimates provided in this work are less conservative and more explicit than previous studies.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Tommaso Toso, Alain Y. Kibangou, Paolo Frasca
Summary: Nowadays, many car drivers use navigation apps to decide which route to take. These apps increasingly rely on real-time data instead of historical data for efficiency. However, due to the necessary steps of data collection, communication, and processing, delay is inevitable. To address this, a macroscopic dynamic traffic assignment model is introduced to describe driver behavior in choosing routes. The model assumes that some drivers follow a navigation app's directions, which are based on delayed traffic data. Through stability analysis, the excessive delay in traffic data is shown and quantified, revealing its negative impact on network efficiency through oscillating trajectories and unsatisfied demand.
IEEE CONTROL SYSTEMS LETTERS
(2023)
Article
Automation & Control Systems
Ron Ofir, Francesco Bullo, Michael Margaliot
Summary: This paper addresses the problem of networked system contraction by designing minimal effort local controllers. The proposed method combines a hierarchical contraction characterization and a matrix-balancing approach to stabilize a Metzler matrix through minimal diagonal perturbations. The approach is demonstrated by designing local controllers that render contractive a network of FitzHugh-Nagumo neurons with general topology of interactions.
IEEE CONTROL SYSTEMS LETTERS
(2022)