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distributed Optimal control of Discrete-Time Linear Systems Over Networks

IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2024年第2期11卷 671-682页

作者： Battilotti, Stefano Cacace, Filippo d'Angelo, Massimiliano Univ Sapienza Rome DIAG Rome I-00185 Italy Univ Campus Biomed Fac Engn Rome Italy

In this article, we consider the distributed linear-quadratic-Gaussian optimal control problem for discrete-time systems over networks. In particular, the feedback controller is composed of local control stations which receive some measurement data from the plant process and regulate a portion of the input signal. We provide a solution when the nodes have information on the structural data of the whole network but take local actions, and when only local information on the network is available to the nodes. The proposed solution is arbitrarily close to the optimal centralized one when the intermediate number of consensus steps is sufficiently large.

关键词： Sensors Optimal control Symmetric matrices Network systems Stability analysis Regulators Process control distributed algorithms/control networked control systems optimal control

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HyNTP: A distributed Hybrid Algorithm for Time Synchronization

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2023年第4期10卷 1744-1756页

作者： Guarro, Marcello D. Sanfelice, Ricardo G. Univ Calif Santa Cruz Dept Elect & Comp Engn Santa Cruz CA 95064 USA

This article presents a distributed hybrid algorithm that synchronizes the time and rate of a set of clocks connected over a network. Clock measurements of the nodes are given at aperiodic time instants, and the controller at each node uses these measurements to achieve synchronization. Due to the continuous and impulsive nature of the clocks and the network, we introduce a hybrid system model to effectively capture the dynamics of the system and the proposed hybrid algorithm. Moreover, the hybrid algorithm allows each agent to estimate the skew of its internal clock in order to allow for synchronization to a common timer rate. We provide sufficient conditions guaranteeing the synchronization of the timers, exponentially fast, with robustness. Numerical results illustrate the synchronization property induced by the proposed algorithm as well as its performance against comparable algorithms from the literature.

关键词： Clocks Synchronization Heuristic algorithms Delays Robustness Hardware Real-time systems Communication networks distributed algorithms/control hybrid systems networked control systems sensor networks

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distributed Hierarchical control for State Estimation With Robotic Sensor Networks

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2018年第4期5卷 2023-2035页

作者： Freundlich, Charles Zhang, Yan Zavlanos, Michael M. Duke Univ Dept Mech Engn & Mat Sci Durham NC 27708 USA

This paper addresses active state estimation with a team of robotic sensors. The states to be estimated are represented by spatially distributed, uncorrelated, stationary vectors. Given a prior belief on the geographic locations of the states, we cluster the states in moderately sized groups and propose a new hierarchical dynamic programming framework to compute optimal sensing policies for each cluster that mitigates the computational cost of planning optimal policies in the combined belief space. Then, we develop a decentralized assignment algorithm that dynamically allocates clusters to robots based on the precomputed optimal policies at each cluster. The integrated distributed state estimation framework is optimal at the cluster level but also scales very well to large numbers of states and robot sensors. We demonstrate efficiency of the proposed method in both simulations and real-world experiments using stereoscopic vision sensors.

关键词： Decision/estimation theory distributed algorithms/control optimal control sensor networks

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Decentralized Moving Horizon Estimation for Large-Scale Networks of Interconnected Unconstrained Linear Systems

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2023年第4期10卷 1855-1866页

作者： Pedroso, Leonardo Batista, Pedro Univ Lisbon Inst Syst & Robot Inst Super Tecn P-1649004 Lisbon Portugal

This article addresses the problem of designing a decentralized state estimation solution for a large-scale network of interconnected unconstrained linear time invariant systems. The problem is tackled in a novel moving horizon estimation (MHE) framework, while taking into account the limited communication capabilities and the restricted computational power and memory, which are distributed across the network. The proposed design is motivated by the fact that in a decentralized setting, a Luenberguer-based framework is unable to leverage the full potential of the available local information. A method is derived to solve a relaxed version of the resulting optimization problem. It can be synthesized offline and its stability can be assessed prior to deployment. It is shown that the proposed approach allows for significant improvement on the performance of recent Luenberger-based filters. Furthermore, we show that a state-of-the-art distributed MHE solution with comparable requirements underperforms in comparison to the proposed solution.

关键词： Estimation Linear systems Couplings control systems Optimization Observers Sensors Decision/estimation theory distributed algorithms/control moving horizon estimation (MHE) networked control systems networks of autonomous agents

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Randomized Gossiping With Effective Resistance Weights: Performance Guarantees and Applications

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2022年第2期9卷 524-536页

作者： Can, Bugra Soori, Saeed Aybat, Necdet Serhat Dehnavi, Maryam Mehri Gurbuzbalaban, Mert Rutgers State Univ Rutgers Business Sch Dept Management & Informat Sci Piscataway NJ 08854 USA Univ Toronto Dept Comp Sci Toronto ON M5S 1A1 Canada Penn State Univ Dept Ind & Mfg Engn University Pk PA 16802 USA

The effective resistance (ER) between a pair of nodes in a weighted undirected graph is defined as the potential difference induced when a unit current is injected at one node and extracted from the other, treating edge weights as the conductance values of edges. The ER is a key quantity of interest in many applications, e.g., solving linear systems, Markov chains, and continuous-time averaging networks. In this article, we consider ERs in the context of designing randomized gossiping methods for the consensus problem, where the aim is to compute the average of node values in a distributed manner through iteratively computing weighted averages among randomly chosen neighbors. For barbell graphs, we prove that choosing wake-up and communication probabilities proportional to ER weights improves the averaging time corresponding to the traditional choice of uniform weights. For c-barbell graphs, we show that ER weights admit lower and upper bounds on the averaging time that improves upon the lower and upper bounds available for uniform weights. Furthermore, for graphs with a small diameter, we can show that ER weights can improve upon the existing bounds for Metropolis weights by a constant factor under some assumptions. We illustrate these results through numerical experiments, where we showcase the efficiency of our approach on several graph topologies, including barbell and small-world graphs. We also present an application of ER gossiping to distributed optimization: we numerically verify that using ER gossiping within EXTRA and DPGA-W methods improves their practical performance in terms of communication efficiency.

关键词： distributed algorithms/control networks of autonomous agents optimization randomized gossiping algorithms

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On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2022年第2期9卷 811-822页

作者： Chakrabarti, Kushal Gupta, Nirupam Chopra, Nikhil Univ Maryland College Pk MD 20742 USA Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a linear model that fits the collective data points. In principle, the agents can apply the decentralized gradient-descent method (DGD). However, when the data matrix is ill-conditioned, DGD requires many iterations to converge and is unstable against system noise. We propose a decentralized preconditioning technique to mitigate the deleterious effects of the data points' conditioning on the convergence rate of DGD. The proposed algorithm converges linearly, with an improved convergence rate than DGD. Considering the practical scenario where the computations performed by the agents are corrupted, we study the robustness guarantee of the proposed algorithm. In addition, we apply the proposed algorithm for solving decentralized state estimation problems. The empirical results show our proposed state predictor's favorable convergence rate and robustness against system noise compared to prominent decentralized algorithms.

关键词： distributed algorithms/control decision/estimation theory local pre-conditioning optimization

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Centrality Measures in Linear Consensus Networks With Structured Network Uncertainties

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2018年第3期5卷 924-934页

作者： Siami, Milad Bolouki, Sadegh Bamieh, Bassam Motee, Nader Lehigh Univ Dept Mech & Mech Engn Bethlehem PA 18015 USA Univ Illinois Coordinated Sci Lab Champaign IL 61801 USA Univ Calif Santa Barbara Dept Mech Engn Santa Barbara CA 93106 USA

We propose new insights into the network centrality based not only on the network graph, but also on a more structured model of network uncertainties. The focus of this paper is on the class of uncertain linear consensus networks in continuous time, where the network uncertainty is modeled by structured additive Gaussian white noise input on the update dynamics of each agent. The performance of the network is measured by the expected dispersion of its states in steady state. This measure is equal to the square of the H-2-norm of the network, and it quantifies the extent by which its state deviates away from the consensus state in steady state. We show that this performance measure can be explicitly expressed as a function of the Laplacian matrix of the network and the covariance matrix of the noise input. We investigate several structures for noise input and provide engineering insights on how each uncertainty structure can be relevant in realworld settings. Then, a new centrality index is defined in order to assess the influence of each agent or link on the network performance. For each noise structure, the value of the centrality index is calculated explicitly, and it is shown how it depends on the network topology as well as the noise structure. Our results assert that agents or links can be ranked according to this centrality index, and their rank can drastically change from the lowest to the highest, or vice versa, depending on the noise structure. This fact hints at emergence of fundamental tradeoffs on network centrality in the presence of multiple concurrent network uncertainties with different structures.

关键词： Centrality measures distributed algorithms/control linear consensus networks networks of autonomous agents network analysis and control social networks stochastic/uncertain systems

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An Algorithm for Resilient Nash Equilibrium Seeking in the Partial Information Setting

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2023年第4期10卷 1645-1655页

作者： Gadjov, Dian Pavel, Lacra Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

Current research in distributed Nash equilibrium (NE) seeking in the partial information setting assumes that information is exchanged between agents that are "truthful." However, in general noncooperative games, agents may consider sending misinformation to neighboring agents with the goal of further reducing their cost. In addition, communication networks are vulnerable to attacks from agents outside the game as well as communication failures. In this article, we propose a distributed NE seeking algorithm that is robust against adversarial agents that transmit noise, random signals, constant singles, deceitful messages, as well as being resilient to external factors such as dropped communication, jammed signals, and man-in-the-middle attacks. The core issue that makes the problem challenging is that agents have no means of verifying if the information they receive is correct, i.e., there is no "ground truth." To address this problem, we use an observation graph, which gives truthful action information, in conjunction with a communication graph, which gives (potentially incorrect) information. By filtering information obtained from these two graphs, we show that our algorithm is resilient against adversarial agents and converges to the NE.

关键词： Games Nash equilibrium Drones Costs Network systems control systems Indexes distributed algorithms/control game theory nonlinear systems optimization sensor networks

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Decentralized Synchronization of Uncertain Nonlinear Systems With a Reputation Algorithm

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2018年第1期5卷 434-445页

作者： Klotz, Justin R. Parikh, Anup Cheng, Teng-Hu Dixon, Warren E. Univ Florida Dept Mech & Aerosp Engn Gainesville FL 32611 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Natl Chiao Tung Univ Dept Mech Engn Hsinchu 300 Taiwan

Decentralized synchronization approaches generally assume that communication of state information between neigh-boring agents is completely accurate. However, just one agent's communication of inaccurate information to neighbors can significantly degrade the performance of the entire network. To help abate this problem, we present a decentralized controller for a leader-follower framework which uses local information to vet neighbors and change consensus weights accordingly. Because updates of the consensus weights produce a switched system, switching control theory techniques are used to develop a dwell-time that must elapse between agents' successive weight updates. A Lyapunov-based stability analysis is presented which develops sufficient conditions for approximate convergence of follower agents' states to a leader agent's time-varying state. Simulation results are provided to demonstrate the performance of the developed techniques.

关键词： Networks of autonomous agents distributed algorithms/control nonlinear systems switched control

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Cooperative Estimation and Robust Synchronization of Heterogeneous Multiagent Systems With Coupled Measurements

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2018年第4期5卷 1597-1607页

作者： Wu, Jingbo Ugrinovskii, Valery Allgoewer, Frank Univ Stuttgart Inst Syst Theory & Automat Control D-70569 Stuttgart Germany Univ New South Wales Canberra Sch Engn & Informat Technol Canberra ACT 2600 Australia

In this paper, we present a distributed estimation setup where autonomous agents estimate their states from coupled measurements, that is, measurements that depend on multiple agents. For instance, in the case of multiagent systems, where only relative measurements are available, this is of high relevance. This paper proposes a distributed observer design solution, which is scalable with respect to the number of agents. This distributed observer is then used for the design of a distributed observer-based output synchronization control algorithm. Robust performance against exogenous and measurement disturbances can be guaranteed for both the estimation error and synchronization error.

关键词： distributed algorithms/control estimation theory networks of autonomous agents robust performance

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