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7th CAA International Conference on Vehicular control and Intelligence, CVCI 2023

作者： Xiang, Jie Li, Yongfu Huang, Longwang Huang, Xin Wang, Xingquan Key Laboratory of Intelligent Air Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9798350340488

This article proposes a hierarchical control framework based on a co-simulation platform in PreScan and CarSim for longitudinal control of connected automated vehicles platoon. First, an upper-level controller based on distributed model predictive control approach that takes into account terminal constraints is designed to output the desired acceleration. Then, with the inverse longitudinal dynamics model of the vehicle and PID tracking controller, the lower-level controller is proposed to output the throttle opening angle and brake pressure by tracking the output of upper-level controller. Besides, this article analyzes the closed-loop system stability of distributed model predictive controller. Finally, a platoon scene with five vehicles was built in PreScan, the co-simulation experiment was carried out jointly with PreScan and CarSim to validate the practical performance of the proposed control framework. © 2023 IEEE.

关键词： CarSim distributed model predictive control Hierarchical control Longitudinal control of vehicle platoon PID PreScan

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Stabilized Neighborhood Optimization based distributed model predictive control for distributed System

Stabilized Neighborhood Optimization based Distributed Model...

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31st Chinese control Conference

作者： Zheng Yi Li Shaoyuan Wu Jie Zhang Xianxia Shanghai Jiao Tong Univ Dept Automat Key Lab Syst Control & Informat Proc Minist Educ China Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Bank China Investment Management Shanghai 200120 Peoples R China Shanghai Univ Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China

ISBN: (纸本)9789881563811

A class of large scale systems, which is naturally divided into many small interacting subsystems with constraints, are usually controlled by a distributed or decentralized control framework. distributed model predictive control (DMPC), in which each subsystem is controlled by a model predictive control (MPC), is a method of choice in the venues of explicitly accommodating constraints, less computational cost and high flexibility. The stability and global performance improvement are the difficulties of DMPC. As an extend of previous work of Neighborhood Optimization based distributed MPC (NO-DMPC), a stabilized NO-DMPC (SNO-DMPC) is proposed. In each subsystem-based MPC, not only the performance of itself but also the performance of its' neighbors are taken as cost function to improve the dynamic performance of entire system with less communication and computational cost. The consistency and stabilization constraints, as will as the bound of them are designed and the dual mode strategy is adopted to guarantee the closed-loop system stabilization. Provided an initially feasible solution can be found, subsequent feasibility of the algorithm is guaranteed at every update, and the asymptotic stabilization is established.

关键词： model predictive control distributed model predictive control distributed system neighborhood optimization

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Optimization Target Resetting distributed model predictive control for Accelerated Cooling Process

Optimization Target Resetting Distributed Model Predictive C...

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10th World Congress on Intelligent control and Automation (WCICA)

作者： Zheng, Yi Li, Shaoyuan Wang, Xiaobo Shanghai Jiao Tong Univ Key Lab Syst Control & Informat Proc Minist Educ China Dept Automat Shanghai Peoples R China Baosteel Iron & Steel Co Ltd Ctr Res & Dev Shanghai 600 Peoples R China

ISBN: (纸本)9781467313988

In accelerated cooling (ACC) processes-large scale systems, since the starting temperature varies along plate, the cooling curves of plate-points are different to each other for obtaining the uniform characteristic of the whole plate. To satisfy the complicated control targets-the various cooling curves, and real-time control requirement, a novel method called Optimization Target Resetting based distributed model predictive control (OTR-DMPC) is proposed. The whole system is divided into many subsystems, and each subsystem is controlled by a local model predictive control (MPC) to decrease the computation cost. The neighborhood optimization is used to coordinate subsystem-based MPC to guarantee the global performance. Meanwhile, the optimization target of each subsystem-based MPC is recalculated in each control period according to the current starting temperature. The experimental results show the efficiency of the proposed method.

关键词： model predictive control distributed model predictive control Accelerated cooling Laminar cooling

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Nash equilibrium-based distributed predictive control strategy for thickness and tension control on tandem cold rolling system

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JOURNAL OF PROCESS control 2021年 97卷 92-102页

作者： Hu, Yunjian Sun, Jie Peng, Wen Zhang, Dianhua Northeastern Univ State Key Lab Rolling & Automat Shenyang 110819 Liaoning Peoples R China

With the increasing demands on strip product quality, conventional control methods cannot break the cold rolling production bottleneck The development of advanced control algorithms provides theoretical support for the improvement of strip accuracy and product stability of the tandem cold rolling process. Considering the complex characteristics of the system, a distributed model predictive control (DMPC) strategy based on the Nash equilibrium is proposed in this study. A state space model including the rolling process with constraints is established. To improve the calculation speed, a Laguerre function is integrated in the control strategy, so as to reduce the parameter dimension. The DMPC online optimal control strategy based on the Nash equilibrium is proposed to solve the problem between the constrained multivariable complex system and online rolling optimization. Its performance and effectiveness are demonstrated through a series of experiments based on rolling data from industry. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Tandem cold rolling Thickness control Tension control Nash equilibrium distributed model predictive control

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Resilient and constrained consensus against adversarial attacks: A distributed MPC framework

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AUTOMATICA 2024年 160卷

作者： Wei, Henglai Zhang, Kunwu Zhang, Hui Shi, Yang Univ Victoria Dept Mech Engn Victoria BC V8W 3P6 Canada Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China

This paper proposes a distributed resilient consensus framework consisting of a distributed model predictive control (DMPC)-based consensus protocol and a new distributed attack detection mechanism, aiming to effectively handle the general linear constrained MAS under adversarial attacks. Based on the historical information from neighbors and a resilience set, we can evaluate the reliability of communication links via the attack detection mechanism. The proposed detection mechanism can significantly reduce the requirement on the network robustness compared with the well-known meansubsequence-reduced (MSR) algorithms. The resilient consensus of general linear constrained MAS with F-locally adversarial attacks is achieved when the communication network is (F + 1)-robust. Furthermore, the DMPC-based resilient consensus framework exhibits the following key feature: the constrained consensus performance is optimized by minimizing a set of control variables. We demonstrate that the recursive feasibility of the associated DMPC optimization problem and the resilient consensus convergence of the constrained MAS can be guaranteed. Finally, the effectiveness of the proposed framework is illustrated through simulation experiments. (c) 2023 Elsevier Ltd. All rights reserved.

关键词： distributed model predictive control Resilient and constrained consensus Multi-agent system Adversarial attacks

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Consensus-Based model predictive control for Active Power and Voltage Regulation in Active Distribution Networks

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ENERGIES 2024年第17期17卷 4490页

作者： Antonelli, Gianluca Fusco, Giuseppe Russo, Mario Univ Cassino & Southern Lazio Dept Elect & Informat Engn Via G Di Biasio 43 I-03043 Cassino Italy

In this paper, a consensus-based model predictive control (Cb-MPC) scheme is proposed to control the active power and voltage at all nodes in grid-connected active distribution networks (ADNs) with multiple distributed energy resources (DERs). The proposed design methodology is based on a multiple-input multiple-output (MIMO) model of an ADN which accounts for both the internal and external interactions among the control loops of the DERs. To achieve the control objective, each DER unit is equipped with a controller-observer system. In particular, the observer implements the consensus algorithm to estimate the collective system state by exchanging data only with its neighbors. The scope of the controller is to solve the MPC optimal problem based on its collective state estimate, and, due to the presence of an integral term in the control action, it is robust against any unknown scenarios of the ADN, which are represented by uncertainty in the model parameters. The results of numerical simulations validate the effectiveness of the proposed method in the presence of unknown changes in the operating conditions of the ADN and of communication using a sample and hold function.

关键词： active distribution networks distributed energy resources MIMO models distributed model predictive control parameter uncertainty simulations

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A Pricing Rule for Third-Party Platoon Coordination Service Provider 13

A Pricing Rule for Third-Party Platoon Coordination Service ...

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13th Asian control Conference (ASCC)

作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Martensson, Jonas KTH Royal Inst Technol Sch Elect Engn & Comp Sci Integrated Transport Res Lab Digital Futures S-10044 Stockholm Sweden KTH Royal Inst Technol Sch Elect Engn & Comp Sci Div Decis & Control Syst S-10044 Stockholm Sweden Shanghai Jiao Tong Univ Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China

ISBN: (纸本)9788993215236

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Platoon coordination pricing rules profit-sharing distributed model predictive control

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distributed Robust Secondary control of Islanded Microgrids: Voltage, Frequency, and Power Sharing

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IEEE TRANSACTIONS ON POWER DELIVERY 2021年第4期36卷 2501-2509页

作者： Mottaghizadeh, Masood Aminifar, Farrokh Amraee, Turaj Sanaye-Pasand, Majid Univ Tehran Coll Engn Sch Elect & Comp Engn Tehran *** Iran KN Toosi Univ Technol Dept Elect Engn Tehran 196976499 Iran

In this paper, a novel distributed robust secondary control is proposed to restore both voltage and frequency in islanded inverter-interfaced microgrids (mu Gs). The proposed method is superior particularly in the disaster ex-post resilient islanded operation of mu Gs where various unknown disruptions and uncertainties exacerbate the successful operation of conventional control schemes. Accordingly, the proposed control scheme is devised so as to accommodate the nonlinearity of mu G and non-ideality of communication networks such as time-varying delays, data packet losses, and link failures. For mu G voltage control, a distributed robust algorithm based on a model predictive control is developed. To do so, the Lyapunov-Razumikhin functional is exploited to analyze the stability of the proposed method, and sufficient conditions are then speculated by the linear matrix inequalities technique. For mu G frequency restoration and achieving accurate active power sharing, a finite-time distributed robust proportional-integral algorithm is presented. The effectiveness of the proposed method is verified by inclusive simulation studies of an islanded mu G in MATLAB/ Simulink.

关键词： Voltage control Frequency control Delays Communication networks Power system stability Power system dynamics Reliability distributed model predictive control feedback linearization secondary voltage and frequency control microgrid

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distributed predictive control of Multi-Agent Systems Based on Error Upper Bound Approach

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IEEE ACCESS 2021年 9卷 11470-11478页

作者： Zhu, Jialin Xue, Binqiang Qingdao Univ Coll Automat Qingdao 266071 Peoples R China Qingdao Univ Shandong Key Lab Ind Control Technol Qingdao 266071 Peoples R China

In this paper, a novel distributed predictive control (DMPC) method for multi-agent systems based on error upper bounds is proposed. To reduce the communication burden, the error upper bound condition between the subsystem and the neighbor subsystems is calculated by introducing the min-max function from the local state error of neighbouring subsystems. Additionally, an improved coupling constraints to describe the relationship between the neighbouring subsystems is introduced. Then, the proposed DMPC algorithm with kinds of the constraints is given, including the terminal cost, the terminal set and the terminal controller. Furthermore, the feasibility of the proposed DMPC algorithm is analyzed and the stability conditions of multi-agent systems are derived. Finally, a numerical example is given to verify the effectiveness of the method.

关键词： Multi-agent systems Upper bound predictive control Couplings Cost function Prediction algorithms Lyapunov methods distributed model predictive control multi-agent systems error upper bound

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Cooperative Online Path Planning for UAVs Based on DMPC and Improved Grey Wolf Optimizer 41

Cooperative Online Path Planning for UAVs Based on DMPC and ...

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第41届中国控制会议

作者： Chuanlong Yang Zhongchang Liu Wei Zhang Wei Yue College of Marine Electrical Engineering Dalian Maritime University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Online path planning for multiple fixed-wing UAVs in 3 D aerial space is a complex optimization problem with high dimension and multiple constraints,which requires efficient solving *** this paper,distributed model predictive control(DMPC) method is adopted to accomplish online path planning for multiple *** order to reduce the computation time of DMPC,an improved grey wolf optimizer(GWO) is designed where pheromone factors are incorporated into GWO to strengthen the exploration ability of the original *** addition,pheromones are optimally selected based on the hierarchy of wolves to guide subsequent iterations so that the convergence speed of the optimizer can be *** examples show the superiorities of the proposed method by comparing with various existing optimizers.

关键词： path planning multiple UAVs distributed model predictive control improved grey wolf optimizer

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