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检索条件"主题词=Distributed Model Predictive Control"

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Cloud-Based DMPC Simulation for Autonomous Mobile Robot Platooning 28

Cloud-Based DMPC Simulation for Autonomous Mobile Robot Plat...

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28th International Conference on System Theory control and Computing

作者： Maxim, Anca Pauca, Ovidiu Lazar, Razvan-Gabriel Amarandei, Cristian-Mihai Caruntu, Constantin-Florin Gheorghe Asachi Tech Univ Iasi Dept Automat Control & Appl Informat Iasi Romania Gheorghe Asachi Tech Univ Iasi Dept Comp Sci & Engn Iasi Romania

ISBN: (纸本)9798350364309;9798350364293

Cloud computing can be an useful tool when dealing with spatially distributed resources, which need to be simultaneously managed. In this work, a simulation environment is developed using OpenStack to apply a distributed model predictive control strategy for a platooning application consisting of multiple autonomous mobile robots. The idea is to develop the entire algorithm by taking advantage of the possibility of creating virtual machines. Thus, each autonomous mobile robot is treated as an individual agent and is modeled and controlled on a virtual machine, whereas the communication between the agents is performed in the cloud, using the TCP/IP protocol standard. The simulation results illustrate that the platooning application deployed in OpenStack outperforms the simulation performed on a single computer.

关键词： cloud computing distributed model predictive control autonomous mobile robots platooning application

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Efficient model predictive control for variable speed limits by optimizing parameterized control schemes 18

Efficient model predictive control for variable speed limits...

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18th IEEE International Conference on Intelligent Transportation Systems

作者： van de Weg, G. S. Hegyi, A. Hoogendoorn, S. P. De Schutter, B. Delft Univ Technol Dept Transport & Planning Delft Netherlands Delft Univ Technol Delft Ctr Syst & Control Delft Netherlands

ISBN: (纸本)9781467365963

This paper proposes an efficient model predictive control strategy that is based on the parameterization of a variable speed limit control scheme. Due to the paramiterization, the solution spaces reduces, which leads to an improved computation time. The parameterized control scheme consists of a speed limited area in which a constant speed limit is imposed. By changing the position of the head and tail of this speed-limited area over time it is possible to change the density and flow in and downstream of this area. The controller optimizes the location of the head and tail of this area over time in such a way that the flow into a bottleneck or jam wave is changed such that congestion can be prevented or resolved. An advantage of this approach is that the complexity of the optimization problem does not increase with an increase in the number of variable speed limit gantries. The controller is tested using a second-order macroscopic traffic flow model. It is shown that the controller improves the total time spent by all the vehicles in the network with 3.7% compared to the no-control situation. This improvement is realized by resolving a jam wave. It is also shown that the controller can achieve a better performance than other model predictive control strategies, when using the same amount of computation time.

关键词： predictive control road traffic control velocity control model predictive control strategy parameterized control scheme optimization second-order macroscopic traffic flow model variable speed control limit scheme Computational modeling Linear programming Mathematical model Optimization predictive models Traffic control Vehicles predictive control Ran Traffic control Velocity control vehicle Variable speed Computational modeling Prediction models computational time linear programming controllers Mathematical model model predictive control parameterization Speed limit distributed model predictive control

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A distributed optimization algorithm for Nash bargaining in multi-agent systems 21st

A distributed optimization algorithm for Nash bargaining in ...

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Camisa, Andrea Koehler, Philipp N. Mueller, Matthias A. Notarstefano, Giuseppe Allgower, Frank Univ Bologna Dept Elect Elect & Informat Engn Alma Mater Studiorum Bologna Italy Univ Stuttgart Inst Syst Theory & Automat Control Stuttgart Germany Leibniz Univ Hannover Inst Automat Control Hannover Germany

In this paper, we consider a multi-objective optimization problem over networks in which agents aim to maximize their own objective function, while satisfying both local and coupling constraints. This set up includes, e.g., the computation of optimal steady states in multi-agent control systems. Since fairness is a key feature required for the solution, we resort to Cooperative Game Theory and search for the Nash bargaining solution among all the efficient (or Pareto optimal) points of a bargaining game. We propose a negotiation mechanism among the agents to compute such a solution in a distributed way. The problem is reformulated as the maximization of a properly weighted sum of the objective functions. The proposed algorithm is then a two step procedure in which local estimates of the Nash bargaining weights are updated online and existing distributed optimization algorithms are applied. The proposed method is formally analyzed for a particular case, while numerical simulations are provided to corroborate the theoretical findings and to demonstrate its efficacy. Copyright (C) 2020 The Authors.

关键词： Cooperative game theory distributed optimization Multi-Objective optimization Nash bargaining distributed model predictive control Network games

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Two-layer model predictive Formation control Of Unmanned Surface Vehicle

Two-layer Model Predictive Formation Control Of Unmanned Sur...

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Chinese Automation Congress (CAC)

作者： Fan, Zhenyuan Li, Huiping Northwestern Polvech Univ Sch Marine Sci & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781538635247

This paper studies the model predictive formation control problems of unmanned surface vehicles (USVs). A two layer model predictive control (MPC)-based formation control strategy is proposed. The proposed formation strategy artificially divides the model of each USV into two layers according to its kinematic model and dynamic model. Using the kinematic model, a distributed MPC algorithm is designed to ensure formation and coordination;with the generated command from the distributed MPC as tracking reference, an MPC is designed 14 the dynamic model to ensure optimal command tracking. Simulation and comparison studies show that the designed algorithm is computational more efficient in comparison with the centralized MPC formation algorithm.

关键词： distributed model predictive control formation control unmanned surface vehicle

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Adaptive Guidance Method Based on distributed MPC of UAV Cluster for Unknown Environment Exploration

Adaptive Guidance Method Based on Distributed MPC of UAV Clu...

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International Conference on Autonomous Unmanned Systems (ICAUS)

作者： Li, Xinpeng Wang, Yue Yin, Hao Zhuang, Xing Li, Xiang Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China

ISBN: (纸本)9789819904815;9789819904792;9789819904785

UAV cluster plays an important role in large-scale complex task, there are still many challenges like the planning and control quantities cannot be properly matched when facing the exploration of large-scale unknown environment with possible obstacles. This paper proposes an adaptive guidance distributed model predictive control (AG-DMPC) exploration method for unknown complex environment of UAV cluster. The control quantity of UAV is directly planned to avoid the conflict between planning quantity and control quantity in traditional methods. The initial solution is generated based on dynamic constraints, and the rolling optimization solution is carried out through the symbiotic biological search algorithm. The evaluation function is constructed by comprehensively considering the growth of exploration rate, cluster collision avoidance and obstacle avoidance, and the adaptive clustering guidance method is introduced to escape local maximum exploration in trap the search process, so as to realize faster exploration of the environment under the condition of ensuring safety constraints. The simulation results show that this method can effectively avoid collision problems, reduce explore lost and escape local traps to improve exploration efficiency.

关键词： Unknown environment exploration UAV cluster distributed model predictive control

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A distributed predictive control Strategy Based on State Estimator for islanded microgrid 8

A Distributed Predictive Control Strategy Based on State Est...

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8th International Power Electronics Conference (IPEC-Niigata) / Energy Conversion Congress and Exposition (ECCE Asia)

作者： Dong, Mi Li, Li Tian, Xiaoyu Cent S Univ Sch Informat Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9784886864055

The traditional droop control is usually used to share real and reactive power without communication for fully decentralization power system. Because of that the traditional droop control has its inherent limitations, this paper presents a modified droop controller based on Kalman filter to reduce load effect, and then utilizes a distributed consensus algorithm to transmit error voltage to other distributed generation (DG) with sparse communication network, and last make use of distributed model predictive control (MPC) to achieve accurately load power sharing between multi-parallel inverters. Simulation results is verified the reliability of the proposed algorithm in realizing load sharing and the voltage-frequency restoration.

关键词： droop control Kalman filter load effect distributed consensus algorithm distributed model predictive control

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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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Traffic Guidance Strategy of Urban Freeways Based on model predictive control 5

Traffic Guidance Strategy of Urban Freeways Based on Model P...

引用

5th International Conference on Transportation Engineering, ICTE 2015

作者： Dong, Kaifan Gu, Jiayue Qiu, Hongtong Yuan, Ye Traffic Management Research Institute of Ministry of Public Security Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Wuxi Jiangsu China

ISBN: (数字)9780784479384

ISBN: (纸本)9780784479384

Urban freeway, as the important carrier of urban transportation, played the role of skeleton in the urban traffic network. It was of vital importance for the entire road network to induce traffic flow of urban freeway reasonably. Firstly, the traffic guidance strategy of urban freeway based on model predictive control was explored. The strategy aimed at minimizing the total time spend. A dynamic expressway network traffic flow model was adopted as the process model. Finally, a simulation case study was presented under different scenarios. The results indicated that the traffic guidance strategy of urban freeway based on model predictive control reduced the total time spent and improved the operational state with good stability and operability. © ASCE.

关键词： Urban freeway model predictive control Total time spend Simulation case Stability urban expressways distributed model predictive control nonlinear model predictive control model predictive control predictive control traffic guidance traffic network Freeway Urban transportation

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distributed Parameterized predictive control for Multi-robot Curve Tracking 21st

Distributed Parameterized Predictive Control for Multi-robot...

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Pacheco, Gabriel, V Pimenta, Luciano C. A. Raffo, Guilherme, V Univ Fed Minas Gerais Grad Program Elect Engn Belo Horizonte MG Brazil Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil

This work proposes a guidance strategy of multiple robots to converge and circulate a curve while avoiding collisions by using a distributed model predictive control. To build the model predictive control framework, systems guided by control laws with parameters are considered, which laws are embedded in the optimization problem. After that, the same problem is distributed using the Alternating Direction Method of Multipliers and nonlinear optimization. To solve the task of convergence and circulation of a closed path, a vector field based control law is embedded in the predictive control scheme. The control law results from the sum of two components, a convergence term and a circulation term, whereas each term has one proportional parameter associated. Numerical results present an application example, and the strategy effectiveness is discussed. Copyright (C) 2020 The Authors.

关键词： Vector fields distributed model predictive control alternating direction method of multipliers multi-robot systems coordination

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Comparison of a primal and a dual decomposition for distributed MPC in smart districts

Comparison of a primal and a dual decomposition for distribu...

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2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Pflaum, Peter Alamir, Mazen Lamoudi, Mohamed Yacine Schneider Elect Ind 37 Quai Paul Louis Merlin F-38000 Grenoble France Univ Grenoble CNRS Gipsa Lab F-38400 St Martin Dhres France

ISBN: (纸本)9781479949342

This paper deals with energy management in smart districts using distributed model predictive control (DMPC). We investigate two decomposition methods, primal and dual decomposition, for problems where a shared resource has to be distributed optimally amongst sub systems. The objective is to compare these two decomposition methods with a focus on how well they are suited in the context of smart district energy management. In primal decomposition a coordinator layer is directly affecting resource limits to the sub problems whereas in dual decomposition virtual prices are used to stimulate the sub areas to change their resource consumption behavior in a desired way. Both methods are demonstrated to be able to converge to the globally optimal energy distribution in simulations, provided that the limit on the shared resource is chosen in a reasonable range. This result is particularly interesting regarding the fact that in the dual decomposition case, the number of degrees of freedom of the coordinator problem is only a fraction of the number of degrees of freedom in primal decomposition.

关键词： distributed model predictive control smart grid primal and dual decomposition

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