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distributed Supply Coordination for Power-to-Gas Facilities Embedded in Energy Grids

IEEE TRANSACTIONS ON SMART GRID 2018年第2期9卷 1012-1022页

作者： Alkano, Desti Scherpen, Jacquelien M. A. Univ Groningen Fac Math & Nat Sci NL-9747 Groningen Netherlands

This paper considers hydrogen and renewable electricity from power-to-gas (PtG) facilities supplied to a gas grid, a mobility sector, and a power grid. The PtG facilities are equipped with hydrogen buffers and fuel cells. The goal is to maximize the expected profit of PtG facilities without exceeding the grid capacities. The decisions on the supply levels are done in a distributed fashion, yet some coordination with the multiple energy grid operators is necessary to obey the grid capacity constraints. The distributed supply coordination is developed using a model predictive control approach based on a dual decomposition combined with the projected gradient method. The approach results in a two-layer optimization problem experienced by each PtG facility and each grid operator. In this way, the grid operators can manage the PtG facilities via dynamic distribution pricing. We study the fairness of the corresponding algorithm and discuss its practical implementation. Simulation results are provided to evaluate the algorithm performance and to investigate the evolution of distribution prices.

关键词： distributed model predictive control distributed generators energy storage intelligent control modeling

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A recursively feasible distributed robust MPC algorithm for vehicle platooning

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IFAC-PapersOnLine 2018年第23期51卷 112-117页

作者： Shi, Shengling Lazar, Mircea Eindhoven University of Technology EindhovenMB5600 Netherlands

This paper considers the design of a feedback robust model predictive control (MPC) algorithm for vehicle platooning. A vehicle platoon is modeled by individual simplified longitudinal dynamics which are coupled through the input of preceding vehicles. The coupled input is regarded as a disturbance and the framework of robust MPC proposed by [Goulart et al., 2006] is adopted for controller design. The main contribution is a feedback robust MPC algorithm with recursive feasibility guarantee in the presence of time–varying disturbance bounds. The proposed algorithm may yield a larger feasible region comparing to the decentralized control scheme, especially when the size of the vehicle platoon increases. Simulations results demonstrate the effectiveness of the distributed MPC algorithm. © 2018

关键词： model predictive control controllers Decentralized control Feedback predictive control systems Robust control Vehicles Constrained controls controller designs distributed model predictive control distributed MPC Feasible regions Longitudinal dynamics Recursive feasibility Vehicle platoons

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Intersection Crossing of Cooperative Multi-vessel Systems

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IFAC-PapersOnLine 2018年第9期51卷 379-385页

作者： Chen, Linying Negenborn, Rudy R. Hopman, Hans Department of Maritime and Transport Technology Delft University of Technology Delft Netherlands

A Cooperative Multi-Vessel System (CMVS) is a system consisting of multiple coordinated vessels. Vessels utilize Vessel-2-Vessel and Vessel-2-Infrastructure communication to making decisions with negotiating and\or collaborating with each other for a common goal. Due to the geographic limitations of banks and navigation rules and regulations, in straight waterways, the cooperation of vessels usually results in train-like formations. This behavior is similar to the highway platooning of vehicles. A particular challenge arises when such platoons have to cross waterway intersections. At the intersections, the vessel trains need to interact with others. However, research on the interaction between vehicle platoons is still lacking. This paper focuses on the cooperation of vessels at waterway intersections. We propose a framework for cooperative scheduling and control of CMVSs at intersections. The actions of the vessels are determined by solving two problems: Waterway Intersection Scheduling (WIS) and Vessel Train Formation (VTF). Firstly, the process of the vessels passing through an intersection is regarded as consumption of space and time. The WIS helps to find a conflict-free schedule for the vessels from different directions. By solving the WIS problem, each vessel's desired time of arrival can be determined. Then, the actions of vessels are determined using a distributed model predictive control algorithm in the VTF problem. Agreement among the vessels is achieved via serial iterative negotiations. Simulation experiments are carried out to illustrate the effectiveness of the proposed framework. We compare the passing time of each vessel, and the total passing time in three scenarios: non-cooperative case, partially-cooperative case, and fully-cooperative case. With the proposed cooperative framework, vessels can have smoother trajectories. The total passing time and the passing time for each vessel also benefit from the cooperation. Besides, the proposed framework

关键词： Problem solving Iterative methods model predictive control predictive control systems Scheduling Traffic control Cooperative frameworks Cooperative Multi vessel System Cooperative scheduling distributed model predictive control Intersection control Non cooperative case Rules and regulations Vehicle platoons

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Optimization-Driven control and Organization of a Robot Swarm for Cooperative Transportation

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IFAC-PapersOnLine 2019年第15期52卷 115-120页

作者： Henrik Ebel Peter Eberhard Institute of Engineering and Computational Mechanics University of Stuttgart Pfaffenwaldring 9 70569 Stuttgart Germany

The cooperation of autonomous robotic systems, forming a robotic network by communicating with each other, brings about the potential to improve both performance and robustness in robotics applications, but introduces additional complexity in control design. In this context, this paper examines a cooperative transportation task that can serve as a test bed for distributed control algorithms, but may also inspire applications in logistics. In the proposed approach, the task solution is split into an organization scheme, determining formations useful for the current situation, as well as a distributed controller maintaining the formation. Both of these rely on the solution of optimization problems, with the latter drawing from distributed model predictive control theory. The optimization problems are formulated in a way that they can be derived automatically from the intrinsic properties of the considered scenario, e.g. the number of participating robots and the shape of the transported object. Therefore, no human intervention or scenario-specific design steps are necessary while still being able to cater to a wide range of scenarios. Challenging simulation scenarios illustrate the performance achievable with the proposed scheme.

关键词： object transportation distributed model predictive control networked robotic systems cooperative control formation control particle swarm optimization

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distributed model predictive control for multi-agent systems with coupling constraints

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INTERNATIONAL JOURNAL OF modelLING IDENTIFICATION AND control 2010年第3-4期10卷 238-245页

作者： Wei ShanBi Ding, Baocang Gang, Chen Yi, Chai Chongqing Univ Coll Automat Chongqing 400030 Peoples R China Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400030 Peoples R China

This paper proposes an improved distributed model predictive control (DMPC) scheme for multi-agent systems with coupling constraints by applying compatibility constraint and deviation penalisation. Firstly, a sufficient condition based on the compatibility constraint to satisfying cooperative coupling constraints is given, which enables control performance and coupling constraints dependent on the compatibility constraint. Then, in order to optimise the control trajectory and to improve the consistency of the actions between agents, the deviation between what an agent is actually doing and what its neighbours believe it is doing is penalised in the cost function. At each sampling instant, the compatibility constraint of each agent is set tighter than the previous sampling instant. The optimal control problem is formulated as quadratic programming with quadratic constraints. Finally, two simulation examples are given to illustrate the effectiveness of the proposed scheme.

关键词： distributed model predictive control DMPC compatibility constraint coupling constraint deviation penalisation

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distributed resource allocation for multi-zone commercial buildings

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Energy Procedia 2019年 158卷 2872-2877页

作者： Jun Mei Xiaohua Xia Department of Electrical Electronic and Computer Engineering University of Pretoria 0002 South Africa

Advanced building structures are extremely complicated with a large number of dynamically interacting components and widely equipped with multi-zone air conditioning (ME A/C) systems. In this paper, multi-zone commercial building systems are built as second order Resistance-Capacitance (RC) models with individual zones communicating to the whole network through neighbors. The presented thermal dynamics are different from that in our previous work [8], which does not consider the wall’s thermal dynamics. The second order RC models are more accurate in capturing the thermal dynamics of a building in comparison with the first order model employed in [8]. We first propose a hierarchical distributed method using ME A/C systems in commercial building for demand response. The idea of the upper layer strategy is based on the balance of building’s energy demand and users’ comfort level to generate reference signals. The lower layer is designed as distributed model predictive controllers (DMPC) to track the reference signals whereas energy cost and demand are reduced. Simulation results are provided to verify the effectiveness of the proposed control.

关键词： ME A/C system distributed model predictive control energy efficiency multi-zone commercial buildings

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Guidance control for Fleet of Small Aerial Robots with Communication Restriction

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IFAC-PapersOnLine 2018年第22期51卷 25-30页

作者： Sasaoka, Takashi Suzuki, Satoshi Shinshu University 3-15-1 Tokida Ueda-shi Nagano386-8567 Japan

In this paper, collision-free guidance control of multiple small aerial robots is designed. Collision avoidance should be considered in the operation of a fleet of aerial robots. A guidance control system using a distributed model predictive control (DMPC) is proposed to realize the collision avoidance. A constraint of the relative position vector between each robot is considered in the design for efficient avoidance. Small multi-rotor helicopter is considered as controlled object, and the guidance control system is designed by using the translational model of the helicopter. The robots exchange information about current state and optimal input sequence each other for calculating the predictive trajectory of others. Based on the calculated trajectories, each helicopter solves its local optimization problem. Here, sharing the velocity information is difficult because calculation processing capability of the small sensor and communication capability among the robots are strictly restricted. Therefore, a dynamic compensator for velocity compensation is introduced. By introducing the dynamic compensator, collision avoidance using only exchange on the position and the input sequence information is accomplished without exchanging velocity information. The effectiveness of the proposed control system is verified by numerical simulations and flight experiment. © 2018

关键词： Air navigation Aircraft control Antennas Collision avoidance Electronic guidance systems Flight control systems Flight simulators Helicopter rotors Helicopters Information dissemination Machine design model predictive control Robots Aerial robots Communication capabilities Communication restrictions distributed model predictive control Guidance control Processing capability Rotor helicopters Velocity compensation

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Experimental Study: Neural Network based model predictive control of a distributed Parameter System

Experimental Study: Neural Network based Model Predictive Co...

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IEEE International Conference on control and Automation

作者： Jay N. Sompura Jaivik K. Mankad Nitin U. Padhiyar Electrical Engineering Department Indian Institute of Technology Chemical Engineering Department Indian Institute of Technology

ISBN: (纸本)9781509017393

An experimental set up has been designed for the purpose of spatial property control of a distributed parameter system. The setup consists of a thin metal chip with four temperature sensors along the length of the chip and four electric heaters to regulate the spatial temperature profile of the metal chip. A sequence of random pulse input signals with varying sampling times for the four manipulated inputs were used for live data generation of the transient temperature values at four locations along the metal chip length. Two data-driven models, namely linear state space model and neural network based model are identified and applied for online control. model predictive control was used to control the spatial temperature profile for set-point tracking and disturbance rejection.

关键词： temperature profiles distributed parameter systems model predictive control predictive control Neural network Computer chips DNA Microarrays Temperature Sensor Device Component data generation State space models Disturbance rejection distributed model predictive control nonlinear model predictive control Metals Set of points

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model predictive control of PMSM Considering Online Parameter Identification

Model Predictive Control of PMSM Considering Online Paramete...

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China International Electrical and Energy Conference (CIEEC)

作者： Hang Ren Wenxiang Song Zhihuang Ruan School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9781728116754

ISBN: (纸本)9781728116761

As a high performance control method, model predictive control has many advantages, such as fast dynamic response, simple structure and ability to deal with multivariables, but its control effect depends on the motor model. Aiming at the problem of the parameter sensitivity of model predictive control, in this paper, a model predictive control considering online parameter identification algorithm is proposed. By establishing model reference adaptive system, and designing the parameter adaptive law base on Popov's Superstability theory, the inductance and flux parameters online identified are updated to the model predictive control. Thus, it solves the problem of model predictive control in parameter mismatch, and realizes high performance control under the motor runs for a long time. The simulation results verify the effectiveness of the proposed method.

关键词： model predictive control(MPC) online parameter identification model reference adaptive system Popov's Superstability theory Parameter identification model reference adaptive control predictive control model predictive control distributed model predictive control nonlinear model predictive control Parameter sensitivity control effect Permanent magnet synchronous machines

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model predictive control for Uncertain Discrete-time T-S Fuzzy Systems via Event-triggered Dynamic Output Feedback Scheme 8

Model Predictive Control for Uncertain Discrete-time T-S Fuz...

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8th IEEE Annual International Conference on Cyber Technology in Automation, control, and Intelligent Systems (IEEE-CYBER)

作者： Tang, Xiaoming Deng, Li Chongqing Univ Posts & Telecommun Coll Automat Key Lab Ind Internet Things & Networked Control Chongqing 400065 Peoples R China

ISBN: (纸本)9781538670576

An event-triggered dynamic output feedback model predictive control method for Takagi-Sugeno(T-S) fuzzy systems with structured uncertainties and bounded disturbances is addressed in this paper. An event-triggered scheme is presented to mitigate the waste of the communication resources due to the unnecessary data packet transmissions. By applying the quadratic boundedness technique and the S-procedure, the parameter dependent fuzzy output feedback controller is presented by online minimizing the upper bound of a quadratic objective function in an infinite time horizon. A numerical example is given to verily the usefulness of the addressed method.

关键词： discrete time systems feedback fuzzy systems infinite horizon predictive control Fuzzy systems predictive control discrete time systems infinite horizon Event trigger Output feedback Feedback communication resources model predictive control distributed model predictive control nonlinear model predictive control

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