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Nash-optimization distributed model predictive control for multi mobile robots formation

PEER-TO-PEER NETWORKING AND APPLICATIONS 2017年第3期10卷 688-696页

作者： Liu, Andong Zhang, Rongchao Zhang, Wen-an Teng, You Zhejiang Univ Technol Coll Informat Engn Zhejiang Prov United Key Lab Embedded Syst Hangzhou 310023 Zhejiang Peoples R China City Univ Hong Kong Dept Elect Engn Kowloon Tong Hong Kong Peoples R China

This paper investigates the distributed model predictive control (DMPC) problem for multi mobile robots. The distributed system model is obtained by the kinematic model of single mobile robot. By including the coupling terms in the cost function, cooperation between subsystems can be incorporated in the distributed control problem. Then, each robot has its own optimal control problem, and neighboring subsystems can exchange information with one another by using wireless communication. The distributed model predictive control problem is formulated by the local cost function and solved by using Nash-optimization algorithm. The convergence condition of the proposed algorithm is presented. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

关键词： distributed model predictive control Multi mobile robots Formation control Nash-optimization

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Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2017年第9期48卷 1891-1901页

作者： Zhu, Kaiqun Song, Yan Zhang, Sunjie Zhong, Zhaozhun Univ Shanghai Sci & Technol Key Lab Modern Opt Syst Dept Control Sci & Engn Shanghai Peoples R China Soochow Univ Sch Iron & Steel Suzhou Jiangsu Peoples R China

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be ***, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

关键词： distributed model predictive control non-fragile observer-based output feedback control convex constraints

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distributed model predictive control for railway traffic management

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2016年第Jul.期68卷 462-489页

作者： Kersbergen, Bart van den Boom, Ton De Schutter, Bart Delft Univ Technol Delft Ctr Syst & Control NL-2600 AA Delft Netherlands

Every day small delays occur in almost all railway networks. Such small delays are often called "disturbances" in literature. In order to deal with disturbances dispatchers reschedule and reroute trains, or break connections. We call this the railway management problem. In this paper we describe how the railway management problem can be solved using centralized model predictive control (MPC) and we propose several distributed model predictive control (DMPC) methods to solve the railway management problem for entire (national) railway networks. Furthermore, we propose an optimization method to determine a good partitioning of the network in an arbitrary number of sub-networks that is used for the DMPC methods. The DMPC methods are extensively tested in a case study using a model of the Dutch railway network and the trains of the Nederlandse Spoorwegen. From the case study it is clear that the DMPC methods can solve the railway traffic management problem, with the same reduction in delays, much faster than the centralized MPC method. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Railway traffic management Dispatching support Mixed integer optimization distributed model predictive control Disturbance management

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Low Complexity distributed model predictive control by Using Contractive Sets

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IFAC-PapersOnLine 2017年第1期50卷 13164-13169页

作者： Grancharova, Alexandra Olaru, Sorin Department of Industrial Automation University of Chemical Technology and Metallurgy Bul. Kl. Ohridski 8 Sofia1756 Bulgaria Laboratory of Signals and Systems CentraleSupélec-CNRS-Université Paris-Sud Université Paris-Saclay 3 Rue Joliot-Curie Gifsur-Yvette Cedex91192 France

In this paper, an approach to low complexity distributed MPC of linear interconnected systems with coupled dynamics subject to both state and input constraints is proposed. The suggested approach is based on the idea of introducing a contractive set constraint in the centralized MPC problem formulation, which would guarantee the closed-loop system stability when using a small prediction horizon. Then, a dual accelerated gradient method is applied to obtain distributedly a suboptimal solution of the resulting Quadratic Programming problem. The suggested approach would be appropriate for embedded distributed MPC since it will reduce the complexity of the on-line MPC computations, simplify the software implementation, and reduce the requirements for available memory. © 2017

关键词： predictive control systems Closed loop systems distributed parameter control systems Gradient methods Large scale systems Linear systems model predictive control Quadratic programming System stability Constraints distributed control distributed model predictive control predictive control Problem formulation Quadratic programming problems Software implementation State and input constraints

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distributed model predictive control for load frequency control with dynamic fuzzy valve position modelling for hydro-thermal power system

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IET control THEORY AND APPLICATIONS 2016年第14期10卷 1653-1664页

作者： Liu, Xiangjie Kong, Xiaobing Lee, Kwang Y. North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Baylor Univ Dept Elect & Comp Engn Waco TX 76798 USA

Reliable load frequency control (LFC) is very important for a modern power system with multi-source power generation and has been the primary focus of studies on advanced control theory and applications. In the LFC of a power system, the generation rate constraints (GRC) and position limit of the governor valve present major challenges to the control scheme because they significantly affect the dynamic responses of the system, resulting in larger overshoot and longer settling time. model predictive control (MPC) is an attractive control strategy that systematically considers the constraints on the process inputs, states, and outputs. It is employed in LFC to cope with the GRC problem. This study proposes a distributed MPC (DMPC) for a four-area hydro-thermal interconnected power system. In the proposed scheme, the limit position of the governor valve is modelled by a fuzzy model and the local predictive controllers are incorporated into the non-linear control system. The effectiveness of the proposed non-linear constraint DMPC was demonstrated by simulations.

关键词： hydrothermal power systems power generation control predictive control distributed control load regulation frequency control valves fuzzy control position control power system interconnection fuzzy set theory distributed model predictive control dynamic fuzzy valve position modelling reliable load frequency control LFC power system multisource power generation advanced control theory generation rate constraints governor valve position limit DMPC four-area hydro-thermal interconnected power system local predictive controllers nonlinear control system

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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 via Proximal Jacobian ADMM for Building control Applications

Distributed Model Predictive Control via Proximal Jacobian A...

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American control Conference

作者： Xiaodong Hou Yingying Xiao Jie Cai Jianghai Hu James E. Braun School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907 USA School of Mechanical Engineering Purdue University West Lafayette IN 47907 USA

ISBN: (纸本)9781509045839

This paper investigates a distributed model predictive control (DMPC) framework for building control applications. The proposed framework is general in that it can be easily customized to solve the dynamic optimization problem for a broad class of multi-zone buildings with relatively complex HVAC systems. The Proximal Jacobian alternating direction method of multipliers (ADMM), a recent variant of the traditional Gauss-Seidel sequential ADMM is employed and adopted to solve the centralized optimization problem, which ultimately leads to an agent-based parallel updating scheme with guaranteed convergence. A case study on the HVAC energy optimization of a multi-zone building is presented to show the effectiveness of the proposed method.

关键词： distributed model predictive control buildings control Jacobian High Voltage Alternating Current Systems

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A Multi-agent Flocking System with Communication Delays via distributed model predictive control 36

A Multi-agent Flocking System with Communication Delays via ...

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第36届中国控制会议

作者： Yanjie Hu Jingyuan Zhan Quan Yuan Xiang Li Adaptive Networks and Control Lab Department of Electronics EngineeringFudan University Research Center of Smart Networks and Systems School of Information Science and EngineeringFudan University

ISBN: (纸本)9781538629185

This paper presents a distributed model predictive algorithm for a multi-agent system with communication delays between *** the agents are dynamically decoupled,which is driven by a local controller relying on the information of its neighbors and *** introduce the waiting mechanism to deal with communication delays,and utilize the distributed model predictive control approach to derive the flocking algorithm for each agent,where the cost function penalizes the state and control efforts as well as the errors between the predicted states and desired *** give a sufficient condition to guarantee the flocking of a multi-agent *** simulations demonstrate the feasibility of the proposed flocking algorithm.

关键词： Flocking Multi-agent system distributed model predictive control Communication delay Lattice structure

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On distributed model predictive control for vehicle platooning with a recursive feasibility guarantee

On distributed model predictive control for vehicle platooni...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Shi, Shengling Lazar, Mircea Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands

This paper proposes a distributed model predictive control algorithm for vehicle platooning and more generally networked systems in a chain structure. The distributed models of the vehicle platoon are coupled through the input of the preceding vehicles. Using the principles of robust model predictive control, the coupled input is regarded as a disturbance and the robust model predictive control algorithm proposed by [Kerrigan, 2001] is employed for every vehicle. Based on this approach, a new distributed model predictive control algorithm is proposed by communicating the inputs among the vehicles, which enlarges the feasible regions of the local controllers while recursive feasibility still holds. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： distributed model predictive control Vehicle platooning Recursive feasibility Constrained control

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Selective distributed model predictive control For Comfort Satisfaction in Multi-Zone Buildings 21

Selective Distributed Model Predictive Control For Comfort S...

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21st International Conference on System Theory, control and Computing (ICSTCC)

作者： Roshany-Yamchi, Samira Witheepanich, Kritchai Escano, Juan M. McGibney, Alan Rea, Susan Cork Inst Technol NIMBUS Ctr Embedded Res Cork Ireland Univ Loyola Andalucia Dept Ingn Seville Spain

ISBN: (纸本)9781538638422

distributed model predictive control (DMPC) for thermal regulation in multi-zone buildings continues to gain attention over centralized approaches. Particularly, centralized control approaches have been shown to become impractical when applied to large-scale buildings due to for example, computation complexity, modeling complexity of large buildings and availability of required sensor and actuator infrastructure. In this paper a novel selective DMPC algorithm is developed in which, each agent optimizes a cost function to minimize the control effort in order to save energy and satisfying the comfort bound. The proposed method is useful especially in building thermal regulation when the objective is to keep the temperature of each zone in the building within the defined comfort bound.

关键词： distributed model predictive control Soft Constraint Building Energy Management Energy Optimization

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