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Binding of Cytotoxic Aβ25-35 Peptide to the Dimyristoylphosphatidylcholine Lipid Bilayer

JOURNAL OF CHEMICAL INFORMATION AND modelING 2018年第5期58卷 1053-1065页

作者： Smith, Amy K. Klimov, Dmitri K. George Mason Univ Sch Syst Biol Manassas VA 20110 USA

A beta 25-35 is a short, cytotoxic, and naturally occurring fragment of the Alzheimer's Afi peptide. To map the molecular mechanism of A beta 25-35 binding to the zwitterionic dimyristoylphosphatidylcholine (DMPC) bilayer, we have performed replica exchange with solute tempering molecular dynamics simulations using all-atom explicit membrane and water models. Consequences of sequence truncation on the binding mechanism have been measured by utilizing as a control our previous simulations probing binding of the longer peptide A beta 10-40 to the same bilayer. The most intriguing feature of A beta 25-35 binding to the DMPC bilayer is a coexistence of two bound states with strikingly different characteristics: a dominant surface-bound state and a less stable inserted state. In the surface-bound state, the peptide samples extended conformations, in which its unbound C-terminal is pointed away from the bilayer. In contrast, in the inserted state, the C-terminal resides deep in the bilayer hydrophobic core. In both states, the N-terminal remains anchored to the bilayer. Free energy landscape analysis reveals that the two states are separated by a moderate barrier, suggesting that A beta 25-35 monomer may frequently interconvert between them. The net effect of A beta 25-35 binding is a minor impact on the bilayer structure, which contrasts with the considerable bilayer perturbations induced by a longer A beta 10-40 peptide penetrating deep into the bilayer core. Therefore, we conclude that the binding mechanisms of A beta 25-35 and A beta 10-40 peptides are different. Potential implications of our results for A beta 25-35 cytotoxicity are discussed. A comparison of experimental data with our findings reveals a good agreement.

关键词： Dimyristoylphosphatidylcholine Peptides Lipid Bilayers distributed model predictive control binding mechanism Countries (nations) Cytotoxicity Binding

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distributed Dual-rate Consensus predictive control of Looper Tension System in Hot Rolling Mills

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INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2018年第2期16卷 577-585页

作者： Zhang, Xiao-Dong Gao, Shao-Shu Liu, Xin-Ping Huang, Ting-Pei China Univ Petr Coll Comp & Commun Engn Qingdao 2666580 Peoples R China

This paper considers a dual-rate distributed predictive control strategy for the looper tension system in hot rolling mills, which is a typical multi-agent system with directed communication topology. First, we establish an interconnected model for looper tension control system and the disturbances from the neighbors are considered effectively. Second, the consensus control protocol is developed based on the proposed control strategy to improve the robustness and stability of the multi-agent, and the sufficient conditions for consensus are developed. We update and implement all the agent controllers sequentially in one output sampling period and begin a new cycle at the next sampling instant, which leads the multi-agent control system is of fast control updating rate and slow output sampling rate. The control inputs of neighbors can be obtained to compensate the coupling effects, and the cooperation of controllers are improved. Finally, simulation results verify the proposed control strategy and corresponding results.

关键词： Consensus control distributed model predictive control dual-rate looper system

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A distributed predictive control of Energy Resources in Radiant Floor Buildings

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JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND control-TRANSACTIONS OF THE ASME 2019年第10期141卷 1-15页

作者： Rastegarpour, Soroush Ferrarini, Luca Palaiogiannis, Foivos Politecn Milan Dipartimento Elettron Informaz & Bioingn Piazza L da Vinci 32 I-20133 Milan Italy Natl Tech Univ Athens Sch Elect & Comp Engn Smart Grids Res Unit Zografos 15780 Greece

This paper studies the impact of using different types of energy storages integrated with a heat pump for energy efficiency in radiant-floor buildings. In particular, the performance of the building energy resources management system is improved through the application of distributed model predictive control (DMPC) to better anticipate the effects of disturbances and real-time pricing together with following the modular structure of the system under control. To this end, the load side and heating system are decoupled through a three-element mixing valve, which enforces a fixed water flow rate in the building pipelines. Hence, the building temperature control is executed by a linear model predictive control, which in turn is able to exchange the building information with the heating system controller. On the contrary, there is a variable action of the mixing valve, which enforces a variable circulated water flow rate within the tank. In this case, the optimization problem is more complex than in literature due to the variable circulation water flow rate within the tank layers, which gives rise to a nonlinear model. Therefore, an adaptive linear model predictive control is designed for the heating system to deal with the system nonlinearity trough a successive linearization method around the current operating point. A battery is also installed as a further storage, in addition to the thermal energy storage, in order to have the option between the charging and discharging of both storages based on the electricity price tariff and the building and thermal energy storage inertia. A qualitative comparative analysis has been also carried out with a rule-based heuristic logic and a centralized model predictive control (CMPC) algorithm. Finally, the proposed control algorithm has been experimentally validated in a well-equipped smart grid research laboratory belonging to the ERIGrid Research Infrastructure, funded by European Union's Horizon 2020 Research and Innovation Prog

关键词： energy resources management thermal energy storage load shifting distributed model predictive control smart buildings

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Scalable Coordinated control of Energy Storage Systems for Enhancing Power System Angle Stability

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2018年第2期9卷 763-770页

作者： Rostami, Mohammadali Lotfifard, Saeed Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA

In this paper, a scalable wide area control scheme using distributed model predictive control is proposed to enhance the angle stability of power systems following large disturbances. In this regard, dynamic model of the local subsystems in the multiarea power system is developed for the model predictive controller and each subsystem is controlled by the associated controller. The controller of each subsystem exchanges minimum information with the controllers of the neighboring subsystems to reach the final result. The proposed controller works based on optimality condition decomposition to coordinate the subsystems. In the proposed wide area control system, the available actuators are mechanical power and field voltage controller of a synchronous generator, and energy storage systems (ESS), which are able to provide synchronizing power support. The performance of the proposed transient stability controller is studied in the New England 68-bus test system. The simulation results demonstrate the effectiveness of the proposed method to improve the angle stability of power systems subsequent to severe disturbances in the system.

关键词： distributed model predictive control power system stability Lagrangian relaxation optimality condition decomposition

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Robust distributed predictive control of Waterborne AGVs-A Cooperative and Cost-Effective Approach

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IEEE TRANSACTIONS ON CYBERNETICS 2018年第8期48卷 2449-2461页

作者： Zheng, Huarong Negenborn, Rudy R. Lodewijks, Gabriel Delft Univ Technol Dept Maritime & Transport Technol NL-2628 CD Delft Netherlands

Waterborne autonomous guided vessels (waterborne AGVs) moving over open waters experience environmental uncertainties. This paper proposes a novel cost-effective robust distributed control approach for waterborne AGVs. The overall system is uncertain and has independent subsystem dynamics but coupling objectives and state constraints. Waterborne AGVs determine their actions in a parallel way, while still minimizing an overall cost function and respecting coupling constraints robustly by communicating within a neighborhood. Our first contribution is the proposal of the system robustness level for the cost-effective robust distributed model predictive control (RDMPC) for waterborne AGVs. Cost-effective RDMPC models the price of robustness by explicitly considering uncertainty and system characteristics in a tube-based robust control framework. The second contribution is an efficient integrated branch & bound (B&B) and the alternating direction method of multipliers (ADMMs) algorithm for solving the cost-effective RDMPC problem. The algorithm exploits special ordered variable sets and combining branching criteria with intermediate ADMM results conducting smart search in B&B. Simulation results demonstrate the effectiveness of the proposed approach for cooperative distributed waterborne AGVs with cost-effective robustness.

关键词： Branch & bound (B&B) cooperative waterborne autonomous guided vessels (waterborne AGVs) cost-effective robustness distributed model predictive control the alternating direction method of multipliers (ADMMs)

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A distributed economic MPC framework for cooperative control under conflicting objectives

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AUTOMATICA 2018年 96卷 368-379页

作者： Koehler, Philipp N. Mueller, Matthias A. Allgoewer, Frank Univ Stuttgart Inst Syst Theory & Automat Control D-70550 Stuttgart Germany

In this paper, we consider the problem of coordinating self-interested interacting dynamical systems by means of a distributed economic MPC framework. The self-interest of the systems is reflected by an individual local objective function each agent is trying to minimize, while cooperation is required with respect to coupling constraints and an asymptotic cooperative goal, which is represented by a particular steady state of the overall system. Our basic premise is that this steady state, which fulfills the cooperative goal, is not known a priori but has to be negotiated online, while already taking control actions. For the purpose of determining this steady state in a distributed way, arbitrary distributed computation algorithms can be incorporated into the proposed framework. We show that satisfaction of coupling constraints and convergence to the desired overall steady state can be established. Examples for an asymptotic cooperative goal include synchronization under conflicting objectives or sensor coverage, which are both studied in the work at hand and are also illustrated by numerical simulations. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： distributed model predictive control Economic model predictive control Collaborative systems

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Accelerated distributed MPC of Linear Discrete-Time Systems With Coupled Constraints

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IEEE TRANSACTIONS ON AUTOMATIC control 2018年第11期63卷 3838-3849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 (MPC) 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 an overall MPC optimization problem involving all systems, which is then solved distributively using a modified distributed Nesterov-accelerated-gradient algorithm. To further reduce the computational requirement, this approach allows for early termination of the distributed gradient algorithm. This is made possible via a consensus algorithm that determines the satisfaction of the termination condition and by appropriate tightening of the coupled constraints. Under reasonable assumptions, the approach is able to produce a suboptimal solution as long as the network of the systems is connected while ensuring recursive feasibility and exponential stability of the closed-loop system. The performance of the proposed approach is demonstrated by a numerical example.

关键词： Consensus algorithm coupled constraints distributed model predictive control Nesterov's method

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A distributed Voltage control Strategy for Multi-Microgrid Active Distribution Networks Considering Economy and Response Speed

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IEEE ACCESS 2018年 6卷 31259-31268页

作者： Dou, Xiaobo Xu, Pei Hu, Qinran Sheng, Wanxing Quan, Xiangjun Wu, Zaijun Xu, Bin Southeast Univ Sch Elect Engn Nanjing 210096 Jiangsu Peoples R China Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA China Elect Power Res Inst Beijing 100192 Peoples R China State Grid Anhui Elect Power Corp Res Inst Hefei 230000 Anhui Peoples R China

This paper presents a novel distributed voltage control strategy to maintain the voltage of active distribution networks containing multiple microgrids. Local voltage regulation characteristics, such as power reserve, adjustment cost, and regulating speed, are identified first. According to a neighbors' voltage regulation characteristics, the microgrid coordinates neighborhood resources and asks them for coordination as soon as voltage problems occur. Microgrids schedule local resources based on a cooperative distributed model predictive control algorithm scheme with neighbor-to-neighbor communication. Tests are performed in an active distribution network with three microgrids. The numerical studies have shown that the proposed strategy mitigates the voltage fluctuation rapidly and efficiently with minimum operating cost.

关键词： Active distribution networks distributed generation distributed model predictive control voltage control

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ALADIN-—An open-source MATLAB toolbox for distributed non-convex optimization

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Optimal control Applications and Methods 2021年第1期43卷

作者： Alexander Engelmann Yuning Jiang Henrieke Benner Ruchuan Ou Boris Houska Timm Faulwasser Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany School of Information Science and Technology ShanghaiTech University Shanghai China

This article introduces an open-source software for distributed and decentralized non-convex optimization named ALADIN- . ALADIN- is a MATLAB implementation of tailored variants of the Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) algorithm. It is user interface is convenient for rapid prototyping of non-convex distributed optimization algorithms. An improved version of the recently proposed bi-level variant of ALADIN is included enabling decentralized non-convex optimization with reduced information exchange. A collection of examples from different applications fields including chemical engineering, robotics, and power systems underpins the potential of ALADIN- .

关键词： ADMM ALADIN decentralized optimization distributed model predictive control distributed optimization nonconvex optimization optimal power flow

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Feasible-Cooperation distributed model predictive control Scheme Based on Game Theory *

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IFAC Proceedings Volumes 2011年第1期44卷 386-391页

作者： Felipe Valencia Jairo J. Espinosa Bart De Schutter Kateřina Staňková Faculty of Mines Universidad Nacional de Colombia Delft Center for Systems and Control The Netherlands

Abstract This work deals with the formulation of a distributed model predictive control scheme as a decision problem in which the decisions of each subsystem affect the decisions of the other subsystems and the performance of the whole system. This decision problem is formulated as a bargaining game. This formulation allows each subsystem to decide whether to cooperate or not depending on the benefits that the subsystem can gain from the cooperation. A solution based on game theory is proposed. The convexity and feasibility properties of the proposed solution are also presented. The proposed control scheme is tested on a case study with a chain of two continuous stirred tank reactors followed by a nonadiabatic flash separator.

关键词： distributed model predictive control game theory bargaining game negotiation model

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