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Subsystem decomposition of process networks for simultaneous distributed state estimation and control

AICHE JOURNAL 2019年第3期65卷 904-914页

作者： Yin, Xunyuan Liu, Jinfeng Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada

An appropriate subsystem configuration is a prerequisite for a successful distributed control/state estimation design. Existing subsystem decomposition methods are not designed to handle simultaneous distributed estimation and control. In this article, we address the problem of subsystem decomposition of general nonlinear process networks for simultaneous distributed state estimation and distributed control based on community structure detection. A systematic procedure based on modularity is proposed. A fast folding algorithm that approximately maximizes the modularity is used in the proposed procedure to find candidate subsystem configurations. Two chemical process examples of different complexities are used to illustrate the effectiveness and applicability of the proposed approach. (c) 2018 American Institute of Chemical Engineers

关键词： subsystem decomposition distributed state estimation distributed control nonlinear process community structure detection

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A new event-triggered distributed state estimation approach for one-sided Lipschitz nonlinear discrete-time systems and its application to wireless sensor networks

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ISA TRANSACTIONS 2023年 137卷 74-86页

作者： Basit, Abdul Tufail, Muhammad Rehan, Muhammad Ahmed, Ijaz Pakistan Inst Engn & Appl Sci PIEAS Dept Elect Engn Islamabad Pakistan

This article proposes the design of a distributed state estimator for a class of one-sided Lipschitz nonlinear systems over wireless sensor networks. The suggested estimation scheme utilizes the one-sided Lipschitz constraint in conjunction with quadratic inner-boundedness, which makes it applicable to a broader class of nonlinear systems. The proposed estimator design is evaluated under a conventional event-triggered mechanism both in the absence and presence of external perturbations. Furthermore, a novel event-triggering condition is introduced that ensures error convergence to the origin in the absence of external perturbations. It is further established that the inclusion of new triggering condition reduces the estimation error upper bounds in the presence of external disturbances and noises. Sufficient conditions for boundedness of estimation errors are derived for each case, and matrix inequalities are developed for the calculation of estimator gains. Finally, a numerical example is considered to illustrate the efficacy of the proposed estimator.& COPY;2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Wireless sensor networks distributed state estimation Event-triggered mechanism One-sided Lipschitz (OSL) Quadratic inner-boundedness

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Event-based distributed state estimation under deception attack

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NEUROCOMPUTING 2017年 270卷 145-151页

作者： Yang, Wen Lei, Li Yang, Chao East China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai Peoples R China

Recently, security issues in wireless sensor networks (WSNs) have attracted lots of attention. It is necessary to design effective measures against the attacker. In this paper, a novel distributed state estimator with an event-triggered scheme is proposed to defend against false data injection attack in WSNs. Here, each sensor detects the rightness of its estimate according to a condition at each time step. When the condition is satisfied, the sensor regards it is not attacked, then it is triggered to send the estimate to its neighboring sensors;Otherwise, the sensor is not triggered. Based on the event-triggered scheme, an optimal estimator gain is designed by minimizing the mean-squared estimation error covariance, and then a sufficient condition is provided to guarantee the stability of the proposed distributed estimator. Finally, a numerical example is provided to illustrate the effectiveness of the proposed estimator with event-based strategy. (C) 2017 Elsevier B.V. All rights reserved.

关键词： distributed state estimation Event-based strategy False data injection attack

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Three-Stage distributed state estimation for AC-DC Hybrid Distribution Network Under Mixed Measurement Environment

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IEEE ACCESS 2018年 6卷 39027-39036页

作者： Kong, Xiangrui Yan, Zheng Guo, Ruipeng Xu, Xiaoyuan Fang, Chen Shanghai Jiao Tong Univ Dept Elect Informat & Elect Engn Shanghai 200240 Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou 310000 Zhejiang Peoples R China State Grid Shanghai Municipal Elect Power Co Elect Power Res Inst Shanghai 200122 Peoples R China

The ac-dc hybrid distribution network is a credible path for the future evolution of distribution network. state estimation is a paramount foundation for the safe and stable operation of the complex distribution network. The application of the centralized state estimation method in an ac-dc distribution network has some obstacles, such as low computational efficiency, large communication capacity, and privacy protection problem. Based on the three-stage state estimation theory, this paper established a three-stage state estimation model for the ac-dc hybrid distribution network integrating supervisory control and data acquisition system and phasor measurement unit. The proposed three-stage estimation model achieves linearization of the nonlinear state estimation for the ac-dc hybrid distribution network. That is, the first and third stages simply solve the linear state estimation problem, and the second stage is a one-step nonlinear transform. Moreover, the alternating direction method of multipliers (ADMM) is applied to solving the distributed problem. Thus, an accurate and efficient three-stage distributed state estimation method for the ac-dc hybrid distribution network is proposed. In this method, ac subsystems and dc subsystems execute state estimation tasks based on local information and eventually achieve the overall consistency of the system state estimation through the transfer iteration of the boundary information, respectively. The combination of bilinear theory and ADMM ensures the convergence of distributed state estimation while improving computational efficiency. The simulation results verified the advantage of the proposal over the existing methods in many aspects.

关键词： distributed state estimation ac-dc hybrid distribution network phasor measurement unit (PMU) three-stage state estimation modeling alternating direction method of multipliers (ADMM)

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Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements

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AUTONOMOUS ROBOTS 2019年第3期43卷 743-768页

作者： Mitra, Aritra Richards, John A. Bagchi, Saurabh Sundaram, Shreyas Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Sandia Natl Labs Auton Hyperson Dept POB 5800 Albuquerque NM 87185 USA

Applications in environmental monitoring, surveillance and patrolling typically require a network of mobile agents to collectively gain information regarding the state of a static or dynamical process evolving over a region. However, these networks of mobile agents also introduce various challenges, including intermittent observations of the dynamical process, loss of communication links due to mobility and packet drops, and the potential for malicious or faulty behavior by some of the agents. The main contribution of this paper is the development of resilient, fully-distributed, and provably correct state estimation algorithms that simultaneously account for each of the above considerations, and in turn, offer a general framework for reasoning about state estimation problems in dynamic, failure-prone and adversarial environments. Specifically, we develop a simple switched linear observer for dealing with the issue of time-varying measurement models, and resilient filtering techniques for dealing with worst-case adversarial behavior subject to time-varying communication patterns among the agents. Our approach considers both communication patterns that recur in a deterministic manner, and patterns that are induced by random packet drops. For each scenario, we identify conditions on the dynamical system, the patrols, the nominal communication network topology, and the failure models that guarantee applicability of our proposed techniques. Finally, we complement our theoretical results with detailed simulations that illustrate the efficacy of our algorithms in the presence of the technical challenges described above.

关键词： distributed state estimation Byzantine attacks Resilient robotic teams Situational awareness

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Parallel Domain-Decomposition-Based distributed state estimation for Large-Scale Power Systems

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2016年第2期52卷 1265-1269页

作者： Karimipour, Hadis Dinavahi, Venkata Univ Alberta Edmonton AB T6G 2V4 Canada

Growing system sizes and complexity, along with the large amount of data provided by phasor measurement units (PMUs), are the drivers to accurate state estimation algorithms for online monitoring and operation of power systems. In this paper, a distributed weighted-least-square state estimation method using an additive Schwarz domain decomposition technique is proposed to reduce the computational execution time. The proposed approach divides a data set into several subsets to be processed in parallel using a multiprocessor architecture considering data exchange among distributed areas. The slow coherency method and balanced partitioning are utilized to reduce the communication overhead and increase accuracy. Moreover, bad data analysis is also investigated in a distributed manner. The performance of the proposed distributed state estimator, along with the speed-up for several test systems, was compared with the traditional centralized state estimator. The simulation results show a speed-up of 6.5 for a 4992-bus system.

关键词： Bad data identification (BDI) distributed state estimation domain decomposition large-scale systems parallel programming phasor measurement units (PMUs) weighted least square (WLS)

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Event-Triggered distributed state estimation Under Unknown Parameters and Sensor Saturations Over Wireless Sensor Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第3期69卷 1772-1776页

作者： Basit, Abdul Tufail, Muhammad Rehan, Muhammad Pakistan Inst Engn & Appl Sci PIEAS Dept Elect Engn Islamabad Pakistan

In this brief, the distributed state and parameter estimation problem is addressed for a class of discrete-time nonlinear systems subject to sensor saturations over wireless sensor networks. In this regard, a novel estimation design is proposed that involves identification of an unknown parameter under event-triggering mechanism. A sufficient condition for exponential uniform ultimate boundedness of estimation error is established using Lyapunov stability theory. The estimator gains to ensure boundedness of error are linked to the solution of inequality constraints. Finally, the effectiveness of proposed estimator is demonstrated using a simulation example.

关键词： Parameter estimation Nonlinear systems Heuristic algorithms estimation error Wireless sensor networks Lyapunov methods Circuit stability distributed state estimation event-triggering unknown parameters sensor saturations sensor networks

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Subsystem Decomposition and Configuration for distributed state estimation

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AICHE JOURNAL 2016年第6期62卷 1995-2003页

作者： Yin, Xunyuan Arulmaran, Kevin Liu, Jinfeng Zeng, Jing Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada Shenyang Univ Chem Technol Liaoning Prov Key Lab Control Technol Chem Proc Shenyang 110142 Peoples R China

distributed state estimation plays a very important role in process control. Improper subsystem decomposition for distributed state estimation may increase the computational burdens, degrade the estimation performance, or even deteriorate the observability of the entire system. The subsystem decomposition problem for distributed state estimation of nonlinear systems is investigated. A systematic procedure for subsystem decomposition for distributed state estimation is proposed. Key steps in the procedure include observability test of the entire system, observable states identification for each output measurement, relative degree analysis and sensitivity analysis between measured outputs and states. Considerations with respect to time-scale multiplicity and direct graph are discussed. A few examples are used to illustrate the applicability of the methods used in different steps. The effectiveness of the entire distributed state estimation configuration procedure is also demonstrated via an application to a chemical process example used in coal handling and preparation plants. (C) 2016 American Institute of Chemical Engineers

关键词： distributed state estimation subsystem decomposition subsystem observability relative degree sensitivity analysis

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Robust distributed state estimation for sensor networks with multiple stochastic communication delays

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2011年第9期42卷 1459-1471页

作者： Liang, Jinling Shen, Bo Dong, Hongli Lam, James Southeast Univ Dept Math Nanjing 210096 Peoples R China Donghua Univ Sch Informat Sci & Technol Shanghai 200051 Peoples R China Harbin Inst Technol Space Control & Inertial Technol Res Ctr Harbin 150001 Peoples R China NE Petr Univ Coll Elect & Informat Engn Daqing 163318 Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Hong Kong Peoples R China

This article is concerned with the robust distributed state estimation problem for a class of uncertain sensor networks with multiple stochastic communication delays. A sequence of mutually independent random variables obeying the Bernoulli distribution is introduced to account for the randomly occurred communication delays. Both the discrete-time target plant and the sensor model are subject to parameter uncertainties as well as stochastic disturbance. The parameter uncertainties are norm-bounded and enter both the system and the measurement matrices. The external stochastic disturbance is given in the form of a scalar Wiener process. Through available output measurements from not only each individual sensor but also its neighbouring sensors, we aim to design distributed state estimators in order to approximate the state of the target plant. By using the Kronecker product, stochastic analysis is carried out to derive a sufficient criterion ensuring the estimation error systems to be convergent in the mean square sense for all randomly occurred delays, admissible stochastic disturbance and parameter uncertainties. Then, an explicit expression of the individual estimator is given in terms of the solution to a convex optimisation problem that can be easily solved by using the semi-definite programme method. A numerical example is given at the end of this article to demonstrate the usefulness of the developed theoretical results.

关键词： distributed state estimation Kronecker product robust estimation sensor networks stochastic perturbation stochastic communication delays

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Sensor network based distributed state estimation for maneuvering target with guaranteed performances

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NEUROCOMPUTING 2022年第0期486卷 250-260页

作者： Zhang, Zheng Dong, Xiwang Han, Liang Li, Qingdong Ren, Zhang Beihang Univ Sch Automat Sci & Elect Engn Sci & Technol Aircraft Control Lab Beijing 100191 Peoples R China Beihang Univ Sch Sino French Engineer Beijing 100191 Peoples R China

This paper proposes a sensor network information fusion based distributed state estimation algorithm for tracking non-cooperative maneuvering target. In order to lower the communication burden and energy consumption, an event-triggered mechanism is introduced. The distributed state estimation algorithm for maneuvering target tracking is designed by two stages, namely, local filtering stage and consensus fusion stage. The algorithm proposed in this paper can be used to obtain the high accurate state estimation of the target by introducing a multiple suboptimal fading factor even when the target makes big maneuvering. Moreover, a contribution factor is designed in the information fusion stage to improve the accuracy of maneuvering target state estimation and reduce the consensus iteration times. Besides, the stochastic boundedness of the event-triggered distributed estimation algorithm is proved by introducing a stochastic process. Finally, Monte Carlo numerical simulation example is designed to illustrate the effectiveness of the algorithm.(c) 2021 Elsevier B.V. All rights reserved.

关键词： Sensor network distributed state estimation Event-triggered mechanism Information fusion Stochastic boundedness

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