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8th IFAC Workshop on distributed Estimation and control in Networked Systems (NECSYS)

作者： Vlahakis, Eleftherios E. Dritsas, Leonidas D. Halikias, George D. City Univ London Sch Math London England ASPETE Dept Elect & Elect Engn Educators Sch Pedag & Technol Educ Athens Greece

A model-predictive scheme for load frequency control of a multi-area power system is proposed. The method depends on a decoupling technique which allows for a control design with a distributed architecture. Treating the total power inflows of each area as input variables, a decoupled linearized model for each area is derived. This allows for the formulation and solution of a model predictive control problem with a quadratic performance index and input saturating constraints on the individual tie-line power flows, along with an overall equality constraint to address the energy balance of the network. It is assumed that the interconnection topology (tie-lines) coincides with the communication topology of the network. The only information which needs to be shared between interconnected areas is the local frequency variables. The effectiveness of the method is illustrated via a simulation study of a three-area network. Future work will attempt to establish formally the stability of the control scheme and to enhance the versatility of the method by including constraints on the state variables. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： distributed model predictive control load frequency control automatic generation control interconnected power system

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A Tube-Based distributed MPC Based Method for Low-Carbon Energy Networks With Exogenous Disturbances

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2025年第1期12卷 381-391页

作者： Jia, Yubin Dong, Zhao Yang Sun, Changyin Meng, Ke Southeast Univ Sch Automat Nanjing 210096 Peoples R China Southeast Univ Key Lab Measurement & Control Complex Syst Engn Minist Educ Nanjing 210096 Jiangsu Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China Anhui Univ Sch Artificial Intelligence Hefei 230601 Peoples R China Univ NSW Sch Elect Engn & Telecommun Sydney NSW 2033 Australia

With the increasing integration of renewable energy into power systems, two key challenges emerge in low-carbon energy networks: the distributed topology resulting from distributed energy resources (DERs), and the fluctuations caused by the intermittency of renewable energy sources (RES). This paper proposes a distributed model predictive control (MPC) for the frequency regulation of low-carbon energy networks that encompass both conventional generators (including hydro and gas turbine power plants) and wind turbines. First, the cooperation based distributed model predictive controller of each subsystem accounts for the communication between the subsystems and global control objectives while the constraints are considered. Second, a tube-based controller containing two cascaded MPCs is proposed to deal with the system exogenous disturbance such as wind speed fluctuation. The simulation cases illustrate the efficiency and the advantages of the proposed method.

关键词： Renewable energy sources Fluctuations Wind speed Power system stability predictive models Wind power generation Stability analysis Generators Wind turbines Frequency control Load frequency control distributed model predictive control tube-based wind power system low-carbon energy networks

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String stability under general topologies for CAVs: A coupled sliding surface-based distributed TMPC approach

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2025年 194卷

作者： Wang, Xuan Qin, Hongmao Bian, Yougang Zhao, Dezong Zheng, Nan Hunan Univ Coll Mech & Vehicle Engn State Key Lab Adv Design & Mfg Technol Vehicle Changsha 410082 Peoples R China Hunan Univ Wuxi Intelligent Control Res Inst WICRI Wuxi 214115 Peoples R China Univ Glasgow James Watt Sch Engn Glasgow City G12 8QQ England Monash Univ Dept Civil Engn Clayton Australia

Connected and Automated Vehicles (CAVs) are critical components of Intelligent Transportation Systems (ITS) to address traffic accidents and congestion and improve fuel economy. It remains an unsolved challenge to guarantee string stability for cooperative control of CAVs under general topologies. This study proposes a distributed tube-based model predictive control (TMPC) approach for string stable cooperative control of CAVs under general topologies by incorporating a novel string stable coupled sliding surface (CSS) as the terminal. This method is less restrictive and has a wider application range than existing string stable methods. First, a novel string stable CSS based on average spacing error and in-neighbor's information is designed to guarantee string stability. Then, a TMPC controller is proposed to enforce the system dynamics to retain on the string stable CSS in a receding horizon manner. Specifically, the cost function, terminal constraints, and terminal assumed control input are appropriately designed to combine the string stable CSS with TMPC. Moreover, feasibility, closed-loop stability, and string stability are theoretically proved. Simulation results show that the proposed controller outperforms the state-ofthe-art distributed model predictive control (DMPC) and TMPC methods in tracking performance and robustness.

关键词： Connected and automated vehicle distributed model predictive control Sliding mode control String stability General topologies

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A Two-Layer Communication Relay Planning Method for a Fixed-Wing UAVs Swarm

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年第5期73卷 7140-7156页

作者： Yin, Dong Yang, Xuan Wang, Chang Yu, Huangchao Chen, Siyuan Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China Northwest Inst Mech & Elect Engn Xianyang 712000 Peoples R China

Communication relay is necessary for a swarm of collaborative Unmanned Aerial Vehicles (UAVs) executing missions in a large area, such as cooperative exploration, mapping tasks and so on, which assists for the quality of transmission in the swarm network. However, it remains a challenge to plan the mission of Relay UAVs (RUs) to enhance communication of the swarm considering the kinematics of UAVs and task sequences of a swarm. This paper proposes a two-layer relay planning framework for a fixed-wing UAV swarm consisting of coarse planning at the Ground control Station (GCS) as well as refined trajectory planning onboard. The GCS planning layer evaluates the relay requirements in the swarm network to generate the initial deployment of RUs, aiming to minimize their numbers while maximizing utility. The beta-weak connectivity model is adopted to evaluate the swarm network topology constructed from the Minimum Spanning Tree (MST). Meanwhile, a Mixed-Integer Nonlinear Programming Problem (MINLP) is employed to determine the initial deployment of RUs including the number and accessing locations. Moreover, the onboard planning layer predicts the states of the Mission UAVs (MUs) connected to the RU using the Kalman filter. Based on these predictions, the trajectories of each RU are autonomously planned online to continuously guarantee stable network connectivity, which is achieved through distributed model predictive control (DMPC). Finally, numerical simulations are conducted to show the effectiveness of the proposed method.

关键词： UAV swarm relay UAV collaborative communication network connectivity distributed model predictive control trajectory planning

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A Multi-Vehicle Self-Organized Cooperative control Strategy for Platoon Formation in Connected Environment

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第3期26卷 4002-4018页

作者： Zhang, Mengqi Wang, Chunyan Zhao, Wanzhong Liu, Jinqiang Zhang, Ziyu Nanjing Univ Aeronaut & Astronaut Dept Vehicle Engn Nanjing 210016 Peoples R China Jiangsu Engn Res Ctr Vehicle Distributed Drive & I Nanjing 210016 Peoples R China

Aiming at the problem of low merging efficiency, poor platoon stability, and high collision risk when multiple connected and automated vehicles merge into the same target platoon, we propose a multi-vehicle self-organized cooperative control strategy for platoon formation, which includes vehicle self-organizing formation control and platoon cooperative merging control. The vehicle self-organizing formation control module organizes the merging vehicles within the V2V communication range into multiple local platoons. The dynamic self-adjusting critical interval and a fixed-topology second-order platoon consistency control protocol are proposed to divided the vehicles reasonably and make the states of local platoon vehicles consistent. The merging vehicles merge into the target platoon as a whole in the form of a local platoon, which transforms the complex multi-vehicle merge problem into a platoon cooperative control problem and improves the merging efficiency. The platoon cooperative merging control module adopts a distributed model predictive control (DMPC) theory to design two longitudinal cooperative merging controllers, which control the target platoon to split to create a merging gap and the local platoon to align with this gap longitudinally. The lateral merging controller controls the local platoon change the lane to merge into the target platoon safely and smoothly. Simulation experiments are conducted in typical scenarios, and it is verified that the proposed control strategy can enable multi-vehicles to merge into a platoon efficiently, safely, and stably.

关键词： Merging Stability analysis Asymptotic stability Optimization Formation control Vehicle dynamics predictive control Prediction algorithms Safety Protocols Connected and automated vehicles multi-vehicle cooperative control platoon formation and control local platoon distributed model predictive control

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distributed model predictive Secondary Voltage control of Islanded Microgrids With Feedback Linearization

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IEEE ACCESS 2018年 6卷 50169-50178页

作者： Lou, Guannan Gu, Wei Sheng, Wanxing Song, Xiaohui Gao, Fei Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China China Elect Power Res Inst Beijing 100192 Peoples R China

This paper presents a novel distributed secondary control method for both voltage and frequency regulation in islanded microgrids. Firstly, the large-signal dynamic model of inverter-interfaced distributed generation (DG) is formulated in the form of a multi-input multi-output nonlinear system, which can be converted to a partly linear one using input-output feedback linearization. Then, the linear-distributed model predictive controller is designated in each DG to realize the secondary voltage control by incorporating the forecasted behaviors of the local and neighboring DG units. Through the receding optimization index of every update process, the implementation of optimal control action accelerates the convergence rate for voltage magnitudes to the reference value. Following, after transforming the nonlinear DG dynamics into a first-order linear system, a distributed proportional integral algorithm is introduced in the frequency restoration while maintaining the accurate active power sharing. Our approach utilizes the distributed architecture, which indicates superior reliability and flexibility compared to the centralized manner;moreover, it can accommodate diverse uncertainties in communication links, model parameters, and time delays. Simulation results are provided to verify the effectiveness of the proposed control methodology.

关键词： Cooperative control distributed model predictive control input-output feedback linearization islanded microgrids secondary control

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Receding optimal synthesis of robust consensus for multi-agent systems with limited communication

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2024年第8期55卷 1493-1509页

作者： Wang, Jie Li, Shaoyuan Shanghai Jiao Tong Univ 800 Dongchuan Rd Shanghai 200240 Peoples R China

A novel strategy based on the robust distributed model predictive control (DMPC) is proposed in this paper to address the consensus of multi-agent systems subjected to unknown-but-bounded disturbances with limited communication range. The proposed strategy utilises the formulation of the tube-based predictive control and has the ability to handle the explicit input constraints and achieve the bounded consensus with initial communication topology preserved under the disturbances. In this proposed strategy, a novel constraint is designed to guarantee the connectivity of the system under the disturbances, and the synthesis methods are proposed for the controller. Meanwhile, it is proved that the proposed algorithm in this paper is recursively feasible, the connectivity can always be preserved and the system can finally reach bounded consensus under the disturbances. A simulation example is provided to demonstrate the proposed robust DMPC-based strategy.

关键词： Consensus multi-agent systems distributed model predictive control connectivity-preserving

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A Novel Cyber-Physical System for the Optimal Heating-Cooling of Buildings

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第4期21卷 6954-6965页

作者： Barzegar, Mahdiyar Farhadi, Alireza Sharif Univ Technol Dept Elect Engn Tehran *** Iran

This paper presents a novel Cyber-Physical System (CPS) equipped with an advanced distributed model predictive control (DMPC) method with reduced order computational complexity, zero steady-state error, reduced start-up energy consumption and improved transient response for the optimal heating-cooling of buildings. The satisfactory application of this method for the optimal heating-cooling of a large-scale (6-story) building with 40 rooms is illustrated. Smart Industrial Internet of Things (IIoT) -based thermostats, a gateway and a general Quadratic Programming (QP) solver are developed. Using this hardware set-up, the simulation results for the 6-story building are verified in a small scale by practical implementation. Note to Practitioners-This paper proposes a novel cyberphysical system for the optimal heating-cooling of large-scale buildings. The proposed system is practical, in particular, for large-scale buildings because for its realization, we do not need mighty and therefore expensive computer servers to execute required optimization problems in real-time. It also has high reliability and resilience due to its distributed computation nature and can be realized using available and cost-effective On-Off electric valves. To implement this system, a general QP solver, smart IIoT-based thermostats and a gateway are designed, developed and implemented in a building for the optimal heating and cooling. The satisfactory performance and superiority of the proposed system in terms of zero steady-state error, transient response, applicability for both heating and cooling systems and limited start-up energy consumption over the traditional as well as more advanced systems are illustrated by simulation and practical implementation.

关键词： distributed model predictive control cyber-physical system building automation and control

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distributed model predictive control with Flexible Communication Networks

Distributed Model Predictive Control with Flexible Communica...

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International Conference on control, Automation and Information Sciences (ICCAIS)

作者： Tri Tran Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW 2007 Australia

ISBN: (纸本)9781467308137;9781467308120

A distributed model predictive control scheme that allows for the communication links between subsystems being either fully connected or partially connected, or totally disconnected is presented in this paper. By incorporating the inner product of manifest variables into the supply rate, an extended input-to-power-and-state stabilisability (IpSS) condition is firstly derived for nonlinear interconnected systems. Dynamic stabilising constraints are subsequently developed for subsystem predictive controllers based on a virtual perturbed-state-feedback strategy that accepts changes in the communication network. The stabilising constraint is rendered by a dissipation-based constraint with respect to manifest variables for nonlinear input-affine systems.

关键词： perturbed state feedback distributed model predictive control input-to-power-and-state stabilisability

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A Two-Stage Framework for CAV Platoon Formation Transformation

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INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY 2025年第3期26卷 729-751页

作者： Yang, Wei Shan Chen, Yue Peng Su, Yi Xin Wuhan Univ Technol Sch Automat Wuhan 430070 Peoples R China

Connected automated vehicle (CAV) platooning transforms intelligent transportation systems but faces challenges in formation changes, including collision avoidance and external traffic interference. We propose a two-stage framework to address these issues. The offline stage employs an A*-based cooperative maneuver algorithm that uses a matrix-based formation representation and simplified vehicle maneuver rules to convert the formation search problem into an optimal path problem, generating discrete intermediate sequences. In the online stage, we introduce a formation-priority-based distributed model predictive control (DMPC) algorithm that maintains interaction consistency among vehicles by assigning priorities based on intermediate formation characteristics. To mitigate long priority chains, our method avoids unnecessary priority comparisons and employs a responsive collision avoidance strategy. Numerical simulations, including experiments with external disturbances, validate that our approach effectively plans intermediate formations. It shows a 9-15% optimality loss compared to centralized MPC and maintains optimality consistency while meeting real-time requirements compared to prioritized DMPC.

关键词： Connected automated vehicle platoon distributed model predictive control Formation control

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