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Average-consensus Tracking for First-order Multi-agent Systems with Quantized Data

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Average-consensus Tracking for First-order Multi-agent Syste...

第32届中国控制与决策会议

作者： Yu Zhang Cheng-Lin Liu Key Laboratory of Advanced Process Control for Light Industry （Ministry of Education） Institute of AutomationJiangnan University

This paper addresses the average-consensus tracking problem of first-order multi-agent systems with constant reference signals via exchanging quantized data,where the topology is balanced and strongly *** transforming the quantized consensus problem into the stability problem,a necessary and sufficient condition is obtained by using matrix analysis theory to guarantee that the multi-agent systems achieve the quantized consensus,and the final consensus state is the average value of constant reference *** simulation examples are provided to illustrate the correctness of the results.

关键词： Constant reference signal Average-consensus tracking Quantized data First-order multi-agent systems

Nonlinear Cooperative Output Regulation with Input Delay Compensation

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arXiv 2024年

作者： Zheng, Shiqi Ahn, Choon Ki Jiang, Xiaowei Yan, Huaicheng Shi, Peng The School of Automation China University of Geosciences Wuhan430079 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Shaoyang Institute of Advanced Manufacturing Technology Shaoyang422000 China The School of Electrical Engineering Korea University Seoul136-701 Korea Republic of The Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology Shanghai200237 China The School of Electrical and Mechanical Engineering The University of Adelaide AdelaideSA5005 Australia

This paper investigates the cooperative output regulation (COR) of nonlinear multi-agent systems (MASs) with long input delay based on periodic event-triggered mechanism. Compared with other mechanisms, periodic event-triggered control can automatically guarantee a Zeno-free behavior and avoid the continuous monitoring of triggered conditions. First, a new periodic event-triggered distributed observer, which is based on the fully asynchronous communication data, is proposed to estimate the leader information. Second, a new distributed predictor feedback control method is proposed for the considered nonlinear MASs with input delay. By coordinate transformation, the MASs are mapped into new coupled ODE-PDE target systems with some disturbance-like terms. Then, we show that the COR problem is solvable. At last, to further save the communication resource, a periodic event-triggered mechanism is considered in the sensor-to-controller transmission in every agent. A new periodic event-triggered filter is proposed to deal with the periodic event-triggered feedback data. The MASs with input delay are mapped into coupled ODE-PDE target systems with sampled data information. Then, Lyapunov-Krasovskii functions are constructed to demonstrate the exponential stability of the MASs. Simulations verify the validity of the proposed results. © 2024, CC BY-NC-ND.

关键词： Feedback control

Distributed Constrained Online Nonconvex Optimization with Compressed Communication

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

Communication Compression for Distributed Nonconvex Optimization

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arXiv 2022年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers distributed nonconvex optimization with the cost functions being distributed over agents. Noting that information compression is a key tool to reduce the heavy communication load for distributed algorithms as agents iteratively communicate with neighbors, we propose three distributed primal–dual algorithms with compressed communication. The first two algorithms are applicable to a general class of compressors with bounded relative compression error and the third algorithm is suitable for two general classes of compressors with bounded absolute compression error. We show that the proposed distributed algorithms with compressed communication have comparable convergence properties as state-of-the-art algorithms with exact communication. Specifically, we show that they can find first-order stationary points with sublinear convergence rate O(1/T) when each local cost function is smooth, where T is the total number of iterations, and find global optima with linear convergence rate under an additional condition that the global cost function satisfies the Polyak–Lojasiewicz condition. Numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2022, The Authors. All rights reserved.

关键词： Iterative methods

A Soft Sensor Prediction Model for NOX Concentration based on AWLS-SVM

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A Soft Sensor Prediction Model for NOX Concentration based o...

Chinese control and Decision Conference, CCDC

作者： Wenjin Yan Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

The nitrogen oxides (NO x ) emissions from coal-fired boilers cause air pollution, and the denitration process has widely used to reduce NO x . Focusing on industrial denitrification with selective catalytic reduction (SCR) in thermal power plant, a soft sensor model has been established by using adaptive weighted least square support vector machine (AWLS-SVM), which aims to predict the mass concentration of NO x . By introducing the criterion of average change of weights, the adaptive adjustment can be guaranteed to converge. Also the parameters of kernel function have been optimized by particle swarm algorithm, which improves the accuracy of the proposed model. Through the validation with industrial process data, the soft-sensing model based on AWLS-SVM method has better prediction ability.

关键词： Predictive models Mathematical model Support vector machines Data models Inductors Fitting Optimization

Improved Sparrow Search Algorithm based DV-Hop Localization in WSN

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Improved Sparrow Search Algorithm based DV-Hop Localization ...

Chinese automation Congress (CAC)

作者： Yin Lei Gu De Liu Fei Key Laboratory of Advanced Control of Light Industry Process Ministry of Education Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

DV-Hop is a widely used positioning technology in WSN. Owing to the problem of low positioning accuracy, based on DV-Hop wireless sensor network positioning technology, an improved sparrow search algorithm (SSA) is presented. The improvement of DV-Hop mainly has two aspects. First, the double communication radius method is adopted to modify the minimum hop count between nodes to reduce the estimated distance error; Secondly, this improved algorithm does not use the commonly used least squares method, but uses SSA to estimate nodes' position; At the same time, SSA applies Levy flight strategy to further improve the performance. Finally, the positioning accuracy of the method in this paper is tested by simulation, and the results prove the superiority of this algorithm.

关键词： Statistics Sociology Mathematical model Prediction algorithms Wireless sensor networks Location awareness Optimization

A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids with Coupled Electricity-Hydrogen-Ammonia under Uncertainties

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arXiv 2024年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2024, CC BY.

关键词： Ammonia

Difference-compensated Consensus Protocol for Platooning of Vehicles with Time Delay

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Difference-compensated Consensus Protocol for Platooning of ...

Chinese control and Decision Conference, CCDC

作者： Hao Guo Cheng-Lin Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This paper investigates the platooning problem of vehicles modeled by double integrators, where the time delay is taken into consideration. A novel difference-compensated consensus protocol is proposed by treating the platooning problem as the consensus problem. The internal stability and string stability are analyzed respectively by using the frequency-domain method, and the sufficient conditions for the asymptotic consensus convergence are gained. Through theoretical analysis, we find that the internal stability of the platooning has no relationship with the time delay, but the string stability is affected by the time delay. Finally, numerical simulation results are carried out to show the effectiveness and performance of the proposed consensus strategy.

关键词： Delay effects Vehicle dynamics Asymptotic stability Numerical stability Stability criteria Protocols

A Novel Method Combining Leader-Following control and Reinforcement Learning for Pursuit Evasion Games of Multi-Agent Systems

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A Novel Method Combining Leader-Following Control and Reinfo...

International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Zhe-Yang Zhu Cheng-Lin Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

In the existing literature, many methods have been utilized in solving the pursuit evasion game. However, most of these methods have one thing in common: all pursuers have to know the evader's position. This paper presents a method combining the multi-agent leader-following control and reinforcement learning, which aims at addressing a pursuit evasion game only when partial pursuers have the knowledge of the position of the evader who moves randomly in two-dimensional grid space. Through decomposing the team task, pursuers realize the encirclement of the evader. Simulation experiment validates the effectiveness of our method.

关键词： Task analysis Games Reinforcement learning Multi-agent systems Robot sensing systems Markov processes automation