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distributed model predictive control approach for cooperative car-following with guaranteed local and string stability

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2019年第Oct.期128卷 69-86页

作者： Zhou, Yang Wang, Meng Ahn, Soyoung Univ Wisconsin Dept Civil & Environm Engn 1415 Engn Dr Madison WI 53706 USA Delft Univ Technol Fac Civil & Geospatial Engn Stevinweg 1 NL-2628 CN Delft Netherlands Univ Wisconsin Civil & Environm Engn 1415 Engn Dr Madison WI 53706 USA

In this paper, a serial distributed model predictive control (MPC) approach for connected automated vehicles (CAVS) is developed with local stability (disturbance dissipation over time) and multi-criteria string stability (disturbance attenuation through a vehicular string). Two string stability criteria are considered within the proposed MPC: (i) the l(infinity)-norm string stability criterion for attenuation of the maximum disturbance magnitude and (ii) l(2)-norm string stability criterion for attenuation of disturbance energy. The l(infinity)-norm string stability is achieved by formulating constraints within the MPC based on the future states of the leading CAV, and the l(2)-norm string stability is achieved by proper weight matrix tuning over a robust positive invariant set. For rigor, mathematical proofs for asymptotical local stability and multi-criteria string stability are provided. Simulation experiments verify that the distributed serial MPC proposed in this study is effective for disturbance attenuation and performs better than traditional MPC without stability guarantee. Published by Elsevier Ltd.

关键词： Connected automated vehicles Longitudinal control distributed model predictive control Local stability l(infinity)-norm string stability l(2)-norm string stability

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distributed model predictive control with hierarchical architecture for communication: application in automated irrigation channels

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INTERNATIONAL JOURNAL OF control 2016年第8期89卷 1725-1741页

作者： Farhadi, Alireza Khodabandehlou, Ali Sharif Univ Technol Dept Elect Engn Tehran Iran

This paper is concerned with a distributed model predictive control (DMPC) method that is based on a distributed optimisation method with two-level architecture for communication. Feasibility (constraints satisfaction by the approximated solution), convergence and optimality of this distributed optimisation method are mathematically proved. For an automated irrigation channel, the satisfactory performance of the proposed DMPC method in attenuation of the undesired upstream transient error propagation and amplification phenomenon is illustrated and compared with the performance of another DMPC method that exploits a single-level architecture for communication. It is illustrated that the DMPC that exploits a two-level architecture for communication has a better performance by better managing communication overhead.

关键词： distributed model predictive control large-scale linear systems networked control system optimisation

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distributed model predictive control for continuous-time nonlinear systems based on suboptimal ADMM

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OPTIMAL control APPLICATIONS & METHODS 2019年第1期40卷 1-23页

作者： Bestler, Anja Graichen, Knut Ulm Univ Inst Measurement Control & Microtechnol D-89081 Ulm Germany

This paper presents a distributed model predictive control (DMPC) scheme for continuous-time nonlinear systems based on the alternating direction method of multipliers (ADMM). A stopping criterion in the ADMM algorithm limits the iterations and therefore the required communication effort during the DMPC solution at the expense of a suboptimal solution. Stability results are presented for the suboptimal DMPC scheme under two different ADMM convergence assumptions. In particular, it is shown that the required iterations in each ADMM step are bounded, which is also confirmed in simulation studies.

关键词： alternating direction multiplier method distributed model predictive control networked systems nonlinear systems stability suboptimality

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distributed model predictive control for nonlinear large-scale systems based on reduced-order cooperative optimisation

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2021年第12期52卷 2427-2445页

作者： Mirzaei, Ahmad Ramezani, Amin Tarbiat Modares Univ Fac Elect & Comp Engn Control Dept Tehran Iran

In this paper, a novel cooperative constrained distributed model predictive control algorithm is proposed to control the nonlinear interconnected constrained large-scale systems. In this algorithm, a novel reduced-order cooperative optimisation approach is proposed which is its main contribution that reconstructs and improves the global cost function of any local controller. In proposed algorithm, each local controller computes its optimal control by minimising the corresponding global cost function which is a combination of its own and its neighbouring subsystems' cost functions. The sufficient conditions are derived to guarantee the recursive feasibility and closed-loop stability specifications to ensure the convergence of the overall states into the positive region which is the neighbourhood of origin. The performance of the proposed algorithm is illustrated via simulation results of a nonlinear large-scale cart-spring-damper system.

关键词： distributed model predictive control interconnected nonlinear large-scale systems reduced-order cooperative optimisation

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distributed model predictive control for vessel train formations of cooperative multi-vessel systems

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2018年第Jul.期92卷 101-118页

作者： Chen, Linying Hopman, Hans Negenborn, Rudy R. Delft Univ Technol Dept Maritime & Transport Technol Delft Netherlands

Recently, the cooperative control of multiple vessels has been gaining increasing attention because of the potential robustness, reliability and efficiency of multi-agent systems. In this paper, we propose the concept of Cooperative Multi-Vessel Systems (CMVSs) consisting of multiple coordinated autonomous vessels. We in particular focus on the so-called Vessel Train Formation (VTF) problem. The VTF problem considers not only cooperative collision avoidance, but also grouping of vessels. An MPC-based approach is proposed for addressing the VTF problem. A centralized and a distributed formulation based on the Alternating Direction of Multipliers Method (ADMM) are investigated. The distributed formulation adopts a single-layer serial iterative architecture, which gains the benefits of reduced communication requirements and robustness against failures. The impacts of information updating sequences and responsibility parameters are discussed. We furthermore analyze the scalability of the proposed method. Simulation experiments of a CMVS navigating from different terminals in the Port of Rotterdam to inland waterways are carried out to illustrate the effectiveness of our method. The proposed method successfully steers the vessels from different origins to form a vessel train. Due to the effective communication, vessels can timely respond to the velocity changes that others make. After the formation is formed, the distances between vessels become constant. The results show the potential to use CMVSs for inland shipping with enhanced safety.

关键词： Cooperative multi-vessel systems Vessel train formation distributed model predictive control Autonomous vessels ADMM

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distributed model predictive control for consensus of nonlinear second-order multi-agent systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2017年第5期27卷 830-842页

作者： Gao, Yulong Dai, Li Xia, Yuanqing Liu, Yuwei Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

This paper proposes a distributed model predictive control algorithm for the consensus of nonlinear second-order multi-agent systems. At each update time, all the agents are permitted to optimize. A positively invariant terminal region and a corresponding auxiliary controller are developed for each agent. Furthermore, time-varying compatibility constraint is presented to denote a degree of consistency between the assumed trajectories and the actual trajectories of each agent. Given the designed terminal ingredients (terminal region, auxiliary controller, and terminal cost) and compatibility constraints, the recursive feasibility and closed-loop stability of the whole system are guaranteed. The simulation results are given to illustrate the effectiveness of the proposed approach. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： nonlinear second-order system distributed model predictive control compatibility constraint invariant terminal region

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distributed model predictive control of vehicle platoons under switching communication topologies

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IMA JOURNAL OF MATHEMATICAL control AND INFORMATION 2023年第4期40卷 638-658页

作者： Chen, Liang Zhan, Jingyuan Zhang, Liguo Beijing Univ Technol Fac Informat Technol Dept Artificial Intelligence & Automat Beijing 100124 Peoples R China Key Lab Computat Intelligence & Intelligent Syst Beijing 100124 Peoples R China

This paper studies the control problem for vehicle platoons under switching communication topologies, where the Predecessor-Following (PF)-failure topology is allowed. Firstly, we design a local optimization problem for each vehicle by using the state information of itself and its neighbouring vehicles, and then present Algorithm 1 based on distributed model predictive control (DMPC). By constructing a common Lyapunov function defined by the joint neighbourhood set, we derive sufficient conditions with respect to the weight matrices in the open-loop optimization problem and the switching topologies for ensuring the stability of the closed-loop system under Algorithm 1. Furthermore, we propose Algorithm 2 by introducing novel constraints into the local optimization problem for each vehicle, which utilize shrinking historical position errors to cope with PF-link failures, such that the string stability of the vehicle platoon is ensured. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed DMPC algorithms for the vehicel platoon under switching communication topologies.

关键词： distributed model predictive control vehicle platoon switching topology string stability

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distributed model predictive control of linear discrete-time systems with local and global constraints

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AUTOMATICA 2017年 81卷 184-195页

作者： Wang, Zheming Ong, Chong Jin Natl Univ Singapore Dept Mech Engn Singapore 117576 Singapore

This paper proposes a distributed model predictive control (DMPC) approach for a family of discrete time linear systems with local (uncoupled) and global (coupled) constraints. The proposed approach is based on the dual problem of a MPC optimization problem involving all systems. This dual problem is then distributedly solved, based on the Alternating Direction Multiplier Method (ADMM) with several known simplifications. When the network of systems is large or sparsely connected, the computation of the optimal control using ADMM can be expensive. The proposed approach mitigates this problem by allowing early termination of the ADMM process. This is made possible via a finite-time consensus algorithm that determines the satisfaction of the termination condition and by appropriate tightening of the coupled constraints. Under reasonable assumptions, the approach is guaranteed to converge to a small neighborhood of the optimal so long as the network is connected. Recursive feasibility and exponential stability of the closed-loop system are shown. The performance of the proposed approach is demonstrated by a numerical example. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： distributed model predictive control Coupled constraints Suboptimality Tightened constraints

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distributed model predictive control for polytopic uncertain systems with randomly occurring actuator saturation and packet loss

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IET control THEORY AND APPLICATIONS 2014年第5期8卷 297-310页

作者： Song, Yan Fang, Xiaosheng Shanghai Univ Sci & Technol Dept Control Sci & Engn Key Lab Modern Opt Syst Shanghai 200093 Peoples R China Zhejiang Normal Univ Coll Math Phys & Informat Technol Jinhua 321004 Zhejiang Peoples R China

In this study, a distributed model predictive control algorithm is presented for the polytopic uncertain system subject to randomly occurring actuator saturation and packet loss. The global system is decomposed into several subsystems, and a novel distributed controller model is established to account for both the actuator saturation and packet loss in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. By transforming the non-linear feedback law into a convex hull of linear feedback laws, the distributed controllers for subsystems are obtained by solving a linear matrix inequality (LMI) optimisation problem. Finally, two simulation examples are employed to show the effectiveness of the techniques proposed in this study.

关键词： distributed control feedback linear matrix inequalities linear systems nonlinear control systems optimisation predictive control uncertain systems distributed model predictive control polytopic uncertain systems randomly occurring actuator saturation packet loss distributed controller model Bernoulli distributed white sequences conditional probabilities nonlinear feedback law convex hull linear feedback laws LMI optimisation problem

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distributed model predictive control Method for Optimal Coordination of Signal Splits in Urban Traffic Networks

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ASIAN JOURNAL OF control 2015年第3期17卷 775-790页

作者： Ye, Bao-Lin Wu, Weimin Mao, Weijie Zhejiang Univ Inst Cyber Syst & Control Natl Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China

Coordination and control approaches based on model predictive control (MPC) have been widely investigated for traffic signal control in urban traffic networks. However, due to the complex non-linear characters of traffic flows and the large scale of traffic networks, a basic challenge faced by these approaches is the high online computational complexity. In this paper, to reduce the computational complexity and improve the applicability of traffic signal control approaches based on MPC in practice, we propose a distributed MPC approach (DCA-MPC) to coordinate and optimize the signal splits. Instead of describing the dynamics of traffic flow within each link of the traffic network with a simplified linear model, we present an improved nonlinear traffic model. Based on the nonlinear model, an MPC optimization framework for the signal splits control is developed, whereby the interactions between subsystems are accurately modeled by employing two interconnecting constraints. In addition, by designing a novel dual decomposition strategy, a distributed coordination algorithm is proposed. Finally, with a benchmark traffic network, experimental results are given to illustrate the effectiveness of the proposed method.

关键词： Urban traffic network distributed model predictive control dual decomposition coordination

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