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9th International Conference on Swarm Intelligence (ICSI)

作者： Ebel, Henrik Eberhard, Peter Univ Stuttgart Inst Engn & Computat Mech Pfaffenwaldring 9 D-70569 Stuttgart Germany

ISBN: (纸本)9783319938189;9783319938172

This paper introduces a distributed control scheme tailor-made to the task of letting a swarm of mobile robots push an object through a planar environment. Crucially, there is no centralized control instance or inter-robot hierarchy, and therefore, all decisions are made in a distributed manner. For being able to cooperate, the robots communicate, although the communication sampling time may be several times longer than the control sampling time. Most characteristic for the approach, distributed model predictive controllers are used to achieve a smooth transportation performance with the predicted control errors utilized to plan a suitable object trajectory. Challenging simulation scenarios show the applicability of the approach to the transportation task.

关键词： distributed optimization Communication Swarm mobile robots Cooperative object transportation distributed model predictive control

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Accelerating space traversal methods for explicit model predictive control via space partitioning trees 13

Accelerating space traversal methods for explicit model pred...

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13th European control Conference (ECC)

作者： Jafargholi, Mahmoud Peyrl, Helfried Zanarini, Alessandro Herceg, Martin Mariethoz, Sebastien ABB Corp Res Baden Daettwil Switzerland ETHZ Automat Control Lab Zurich Switzerland

ISBN: (纸本)9783952426913

The paper elaborates an approach for acceleration of space traversal methods for solving a point location problem involved in the evaluation of explicit model predictive control laws. The idea is to improve the initialisation of the space traversal algorithms by providing initial estimates that restrict the search over a fraction of the original space. The reduction of the search space ensures that the space traversal algorithms can find the solution significantly faster as if sought over the full space. The proposed approach comprises two algorithms. The first algorithm generates an orthogonal partition of the search space off-line which is represented by a quadtree. In the second algorithm, the quadtree is traversed on-line and a particular space traversal method is initialised. The paper provides complexity analysis of both algorithms in the runtime and storage requirements. The approach is tested numerically on multiple examples and achieves significant reduction of iterations in the space traversal methods.

关键词： Acceleration Aerospace electronics Complexity theory Indexes Legged locomotion Memory management Partitioning algorithms avionics Partitioning algorithms acceleration Biped locomotion Store management Complexity theory quaternary tree model predictive control predictive control distributed model predictive control nonlinear model predictive control

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Prediction-based Transmission-control Codesign for Vehicle Platooning 92

Prediction-based Transmission-Control Codesign for Vehicle P...

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92nd IEEE Vehicular Technology Conference (IEEE VTC-Fall)

作者： Hu, Yuying Chen, Cailian He, Jianping Yang, Bo Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9781728194844

The advancements in automation and vehicular communication have enabled the platoon systems. The vehicles in a platoon are dynamically decoupled but constrained by spatial geometry. To coordinate decisions and act cooperatively, information sharing among vehicles is required, which means the platooning problem involves both communication and control issues. We consider a communication resource-aware control problem for platoon systems in this paper. To provide desirable driving performances and flexible communication scheduling opportunities for platoon systems, the distributed model predictive control (DMPC) method and communication trigger mechanism are jointly designed, which yields the communication-aware DMPC (CA-DMPC) algorithm. Simulations have been conducted to demonstrate the satisfactory control performances and significant communication savings.

关键词： Platoon network resource-aware distributed model predictive control communication-trigger

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distributed Economic MPC with Safety-Based Constraints for Nonlinear Systems

Distributed Economic MPC with Safety-Based Constraints for N...

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

作者： Albalawi, Fahad Durand, Helen Christofides, Panagiotis D. Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA Univ Calif Los Angeles Dept Chem & Biomol Engn Los Angeles CA 90095 USA

Promoting process safety of chemical processes while operating them in an economically-optimal manner is a matter of great importance. In Albalawi et al. (2016), a safety-based economic model predictive control methodology (safety-EMPC) was developed to operate nonlinear processes in an economically-optimal manner while maintaining process safety and closed-loop stability. However, the safety-EMPC control strategy was developed with a centralized economic model predictive control (EMPC) structure;thus, computation time limitations within a sampling period may reduce the effectiveness of such a controller design for promoting process safety. Alternatively, we develop in this work sequential and iterative safety based distributed EMPC schemes (safety-DEMPC) that may overcome the computation time limitations of the centralized safety-EMPC while maintaining similar closed-loop performance. Using a catalytic reactor example, the two proposed safety-DEMPC schemes were demonstrated to achieve similar closed-loop performance to the centralized safety-EMPC while reducing the on-line computation time requirements compared to the centralized safety-EMPC. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Process safety distributed model predictive control computation time

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Partitioning for Large-scale Systems: A Sequential distributed MPC Design

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IFAC-PapersOnLine 2017年第1期50卷 8838-8843页

作者： Barreiro-Gomez J. Ocampo-Martinez C. Quijano N. Automatic Control Department Universitat Politècnica de Catalunya Institut de Robòotica i Informàtica Industrial (CSIC-UPC) Llorens i Artigas 4-6 Barcelona 08028 Spain Departamento de Ingeniería Electrica y Electrónica Universidad de los Andes Carrera 1 No 18A-10 Bogotá Colombia

Large-scale systems involve a high number of variables making challenging the design of controllers because of information availability and computational burden issues. Normally, the measurement of all the states in a large-scale system implies to have a big communication network, which might be quite expensive. On the other hand, the treatment of large amount of data to compute the appropriate control inputs implies high computational costs. An alternative to mitigate the aforementioned issues is to split the problem into several sub-systems. Thus, computational tasks may be split and assigned to different local controllers, letting to reduce the required time to compute the control inputs. Additionally, the partitioning of the system allows control designers to simplify the communication network. This paper presents a partitioning algorithm performed by considering an information-sharing graph that can be generated for any control strategy and for any dynamical large-scale system. Finally, a distributed model predictive control (DMPC) is designed for a large-scale system as an application of the proposed partitioning method. © 2017

关键词： distributed model predictive control large-scale systems Partitioning

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A MULTI-AGENT MPC ARCHITECTURE FOR distributed LARGE SCALE SYSTEMS

A MULTI-AGENT MPC ARCHITECTURE FOR DISTRIBUTED LARGE SCALE S...

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2nd International Conference on Agents and Artificial Intelligence (ICAART 2010)

作者： Javalera, Valeria Morcego, Bernardo Puig, Vicenc CSIC UPC Inst Robot & Informat Ind Adv Control Syst Grp C Llorens & Artigas 4-6 Barcelona 08028 Spain

ISBN: (纸本)9789896740214

In the present work, techniques of model predictive control (MPC), Multi Agent Systems (MAS) and Reinforcement Learning (RL) are combined to develop a distributed control architecture for Large Scale Systems (LSS). This architecture is multi-agent based. The system to be controlled is divided in several partitions and there is an MPC Agent in charge of each partition. MPC Agents interact over a platform that allows them to be located physically apart. One of the main new concepts of this architecture is the Negotiator Agent. Negotiator Agents interact with MPC Agents which share control variables. These shared variables represent physical connections between partitions that should be preserved in order to respect the system structure. The case of study, in which the proposed architecture is being applied and tested, is a small drinking water network. The application to a real network (the Barcelona case) is currently under development.

关键词： Large scale systems Multi agent systems distributed model predictive control Reinforcement learning

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A Heated Needle Micromanipulator with Hybrid control for Heat-Caused Denaturation in Proteins

A Heated Needle Micromanipulator with Hybrid Control for Hea...

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IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

作者： Boksuwan, Sungwan Benjanarasuth, Taworn Aoyama, Hisayuki King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok Thailand Univ Electrocommun Dept Mech Engn & Intelligent Syst Chofu Tokyo 182 Japan

ISBN: (纸本)9781467391078

The paper proposes a micromanipulator with the heated needle as an end effector in order to transfer heat around a micro area of a sample, egg whites. The proposed micromanipulator is controlled by a combination of an explicit model predictive control and PID controller, so-called the hybrid control, to accomplish tracking performances of several reference paths or shapes of heating the specific area. A tungsten needle wrapped with nichrome wire is used as a heat source mechanism and is connected to the two dimensional micromanipulator. The experimental results reveal that the heated needle can provide high temperature up to 50 degrees C with 1 0 mu m needle tip diameter. In addition, the results indicate the effective operations for a point heating and denaturing egg whites in micro scale. Moreover, the heated needle is able to heat along the desired paths (a circle, ellipse, square or triangle) with the error less than 2 mu m from the center of measurement.

关键词： micromanipulator hybrid control NEEDLES end effectors Egg White Heating heat denaturation Proportional Integral Derivative control distributed model predictive control nonlinear model predictive control Triangle Proteins

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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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Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration

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High-Speed Railway 2024年第3期2卷 143-152页

作者： Xiaolin Luo Tao Tang Le Wang Hongjie Liu State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China Department of Electrical and Computer Engineering University of CaliforniaRiversideCA 92521USA Beijing Zongheng Electro-Mechanical Technology Development Co. Ltd.Beijing 100081China School of Automation and Intelligence Beijing Jiaotong UniversityBeijing 100044China National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong UniversityBeijing 100044China

The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe *** guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB *** this case,the minimal safety distance is usually numerically calculated without an analytic ***,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing *** solve this problem,we propose a distributed Economic model predictive control(DEMPC)approach with computation efficiency and theoretical ***,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved *** theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient ***,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among ***,experimental results demonstrate the performance and advantages of the proposed approaches.

关键词： Virtually coupled train set Space-time separation Economic model predictive control distributed model predictive control Emergency braking configuration

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Feedback Approximation in model predictive control

Feedback Approximation in Model Predictive Control

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2015 International Conference "Stability and control Processes" in Memory of V.I. Zubov (SCP)

作者： Ponomarev, Anton St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9781467376983

model predictive control of a nonlinear dynamical system with linearizable and Lipschitz right-hand side is studied. It is proven that the exact model predictive control feedback allows approximation with a piecewise-affine, possibly discontinuous, function defined by its precalculated values on a finite grid. Approximation is understood not in the sense that control values are close but rather in the sense of closeness of the cost values. Additionally, if such approximation is close enough, stability of the approximate MPC is proven.

关键词： approximation model predictive control predictive control distributed model predictive control nonlinear model predictive control Nonlinear dynamical systems Intimacy Feedback Discontinuous Function

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