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

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A Renewable Energy Integration Application in a MicroGrid Based on model predictive control

A Renewable Energy Integration Application in a MicroGrid Ba...

引用

IEEE Power and Energy Society General Meeting

作者： Jingran Ma Fang Yang Zhao Li S. Joe Qin the Department of Chemical Engineering and Materials Science University of Southern California Los Angeles CA 90089 USA During this work ABB US Corporate Research Center Raleigh NC 27606 USA the Department of Chemical Engineering and Materials Science and Department of Electrical Engineering University of Southern California Los Angeles CA 90089 USA

ISBN: (纸本)9781467327275

This paper investigates the application of model predictive control (MPC) method in a MicroGrid with distributed energy resources (DERs), including distributed generators, energy storage and demand response to achieve higher penetration of renewable energy. A MicroGrid is an aggregation of network that is connected to a centralized grid and can be operated autogenously. MPC utilizes a simulation model to make decisions on the amount of power that the MicroGrid should draw from the connected main grid and each DER respectively, in a way that the economical cost is minimized and all operational constraints are satisfied. The potential of MPC is shown by simulations on an IEEE test feeder modeled on the OpenDSS simulator.

关键词： MicroGrid renewable energy model predictive control simulation OpenDSS MICRO-GRID Maximum Allowable Concentration model predictive control Simulation models predictive control distributed model predictive control nonlinear model predictive control Demand-Responsive Renewable energy OPERATING LIMIT

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Economic model predictive control of the electric arc furnace using data-driven multi-rate models

Economic model predictive control of the electric arc furnac...

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American control Conference

作者： Mudassir M. Rashid Prashant Mhaskary Christopher L.E. Swartz Dept. of Chemical Engineering McMaster University Hamilton Ontario Canada L8S 4L7

ISBN: (纸本)9781467386838

This work considers the problem of economic model predictive control (EMPC) of electric arc furnaces (EAF), subject to the limited availability of process measurements and noise. The key issues addressed are: (1) the multi-rate sampling of process variables;and (2) the requirement of optimized operation that achieves desired product specifications and also minimizes the operating costs. To this end, we identify data-driven models that capture the temporal dynamics of process measurements sampled at different rates. The resulting multi-rate models are used to design a two-tiered predictive controller that enables achieving the target end-point while minimizing the associated costs. The EMPC is implemented on the EAF process and the closed-loop simulation results illustrate the improvement in economic performance over existing trajectory-tracking approaches.

关键词： Steel Process control Economics Computational modeling Slag Temperature measurement predictive models Arc furnaces temperature measurement Computational modeling Process control Prediction models slag economics Steels Economic models predictive control data driven Optimal operation distributed model predictive control nonlinear model predictive control

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model predictive control for dynamic positioning system of ships with unknown time-varying disturbances and actuator constraint

Model predictive control for dynamic positioning system of s...

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International Conference on Information Science and Technology (ICIST)

作者： Guibing Zhu Jialu Du Yongchao Liu College of Information Science and Technology Dalian Maritime University Dalian China

This paper proposes a disturbance compensating model predictive control (DCMPC) strategy for the dynamic positioning (DP) system of ships with unknown time-varying environmental disturbances and actuator saturation. The proposed strategy can make the position and heading of the dynamically positioned ship converge to the desired values without any priori knowledge about environmental disturbances. The extended state observer (ESO) is introduced to estimate the unknown environmental disturbances. Based on ESO, the DCMPC algorithm is proposed to deal with the unknown disturbances. Finally, the simulations are carried out on a dynamically positioned ship and simulation results show the effectiveness of the proposed control strategy.

关键词： disturbance compensating dynamically positioned ships extended state observer model predictive control Ships model predictive control predictive control distributed model predictive control nonlinear model predictive control Observers Dynamic positioning control strategy Unknown actuators time varying European standardisation body DP system

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model predictive control of a high speed switched reluctance generator system

Model predictive control of a high speed switched reluctance...

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European control Conference

作者： Sava Marinkov Bram de Jager Maarten Steinbuch Department of Mechanical Engineering Eindhoven University of Technology

ISBN: (纸本)9781479901890

This paper presents a novel voltage control strategy for the high-speed operation of a Switched Reluctance Generator. It uses a linear model predictive control law based on the average system model. The controller computes the DC-link current needed to achieve the tracking of a desired voltage reference in the presence of an unknown electrical load current. Its output is converted into a pair of excitation angles (turn-on/turn-off) by means of optimized scaling and mapping, while minimizing the dominant high-speed power loss. The constraints on the average DC-link voltage and current signals are directly handled. A numerical example is provided to validate the effectiveness and the robustness of the proposed control scheme.

关键词： Reluctance generators predictive control voltage reference High-speed operation DC link model predictive control distributed model predictive control nonlinear model predictive control numerical example High speed control law

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model predictive control of MEMS LCR

Model Predictive Control of MEMS LCR

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Annual Conference of the IEEE Industrial Electronics Society

作者： Amardeep Singh Afshin Izadian Sohel Anwar Energy Systems and Power Electronics Laboratory Purdue School of Engineering and technology IUPUI

ISBN: (纸本)9781479902255

This paper illustrates the application of model predictive control for trajectory control of micro electro mechanical lateral comb resonators (MEMS LCRs). A recursive least square estimator with dynamic data weighting method is used to estimate the parameters of MEMS in real-time. Accordingly, the control law and the gains are derived to achieve high performance trajectory control. Simulation results demonstrate a close trajectory profile tracking and accurate parameter estimation performance.

关键词： Microelectromechanical systems trajectory control distributed model predictive control nonlinear model predictive control model predictive control predictive control Parameter estimation control law Vincristine Gain

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Combining pharmacological therapy and vaccination in Chronic Myeloid Leukemia via model predictive control

Combining pharmacological therapy and vaccination in Chronic...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Marco Laurino Maurizio Stano Monica Betta Gabriele Pannocchia Alberto Landi Department of Surgical Medical Molecular Pathology and of Critical Area University of Pisa Department of Information Engineering (DIE) University of Pisa Department of Civil and Industrial Engineering University of Pisa Extreme Centre Scuola Superiore Sant'Anna

ISBN: (纸本)9781457702150

This paper describes a simulation study which aims at optimizing the therapy for the control of Chronic Myeloid Leukemia according to the following objectives: the reduction of the administered drug and vaccine amounts, the establishment of a auto-immune response and the long-term control of disease without reducing the effective of therapy with respect to the full treatment. A therapy optimization method is developed defining and solving a model predictive control algorithm, preceded by an accurate Initial Guess search based on Monte-Carlo like approach. Simulation results show that the suggested procedure achieves the proposed goals.

关键词： Chronic Myeloid Leukemia predictive control Medicine Myeloid leukemia model predictive control Prophylactic vaccination distributed model predictive control nonlinear model predictive control

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Economic model predictive control for scheduled switching operations

Economic model predictive control for scheduled switching op...

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American control Conference

作者： Su Liu Jinfeng Liu Department of Chemical & Materials Engineering University of Alberta Canada T6G 1H9

ISBN: (纸本)9781467386838

In this work, we consider economic model predictive control (EMPC) for scheduled switching operations. The proposed EMPC scheme takes advantage of a set of auxiliary controllers that locally stabilizes the optimal steady state of each operating mode. In the proposed approach, EMPC operations are divided into two phases - an infinite-time operation phase and a mode transition phase, depending on the current sampling time and the scheduled mode switching time. The proposed EMPC design is computationally efficient and enjoys enlarged feasibility regions than the auxiliary controllers. Sufficient conditions to ensure recursive feasibility of the proposed EMPC design are established. Simulation results of a chemical process example demonstrate the applicability and effectiveness of our approach.

关键词： Switches Schedules Steady-state Economics Asymptotic stability Switched systems Switched systems asymptotic stability region Switches Steady state economics switching operation Economic models predictive control distributed model predictive control nonlinear model predictive control operation mode Chemical processes

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predictive Energy Management Strategy for Fully Electric Vehicles based on Hybrid model predictive control

Predictive Energy Management Strategy for Fully Electric Veh...

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American control Conference

作者： Shuwei Zhang Yugong Luo Keqiang Li Junmin Wang Department of Mechanical and Aerospace Engineering The Ohio State University Columbus OH 43210 USA State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 China

ISBN: (纸本)9781509045839

Limited travelling range is a major concern for fully electric vehicles (FEVs), and enlarging the total driving range is a main research topic of FEVs. Recently, with the development of intelligent transportation systems, traffic information can be available for the vehicle control systems, like terrain profile and velocity and acceleration of preceding vehicles. With such information, energy-efficient control for FEVs could further prolong the total driving range. In this paper, a hybrid model predictive control method is introduced to control an FEV considering the road terrain profile ahead and preceding vehicle movement information. With the vehicle-to-vehicle wireless communication technology, the movement of preceding vehicle can be predicted in each control cycle. While keeping a suitable distance from the preceding vehicle, the driving energy consumption is optimized. Simulation results show that this method has a better energy saving performance than the traditional methods under various driving conditions even with communication packet losses.

关键词： fully electric vehicles energy efficient control hybrid model predictive control all-electric Hybrid modes vehicle Energy management control period distributed model predictive control nonlinear model predictive control predictive control Packet loss control systems FEV gene Forced Expiratory Volume

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model predictive control using affine disturbance feedback for constrained linear system

Model Predictive Control using affine disturbance feedback f...

引用

Proceedings of the 46th IEEE Conference on Decision and control, Pages 3220-3677

作者： C. Wang C.J. Ong Melvyn Sim Department of Mechanical Engineering National University of Singapore Singapore Singapore-MIT Alliance Department of Mechanical Engineering National University of Singapore Alliance Singapore Singapore-MIT Alliance Business School National University of Singapore Alliance Singapore

ISBN: (纸本)9781424414970;1424414970

This paper proposes a control parametrization under model predictive control framework for constrained linear discrete time systems with bounded additive disturbances. The proposed approach has the same feasible domain as that obtained from parametrization over the family of time-varying state feedback policies. Under the proposed control law, the closed-loop system is stable in the sense that the state converges, in time, to a bounded set that has a characterization determined by a feedback gain.

关键词： Linear system model predictive control predictive control feedback gain parameterization State feedback Affine In-law control law distributed model predictive control nonlinear model predictive control Bounded discrete time systems Feedback

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A Study of a Gun-Turret Assembly in an Armored Tank using model predictive control

A Study of a Gun-Turret Assembly in an Armored Tank using Mo...

引用

2009 American control Conference (ACC 2009)

作者： Gautam Kumar Pradeep Y. Tiwari Vincent Marcopoli Mayuresh V. Kothare Chemical Process Modeling and Control Center Department of Chemical Engineering Lehigh University Bethlehem PA 18015 U.S.A. Process Dynamics and Optimization group Bayer Technology Services Americas 8500 W Bay Rd Baytown TX 77523 U.S.A. General Dynamics Land Systems Sterling Hts. MI 48310 U.S.A.

ISBN: (纸本)9781424445233

Operation of the gun/turret system in a military tank is limited by several constraints some of which are posed by obstacles existing on the vehicle's own platform. These mechanical constraints acting as hard constraints can cause serious damage to the whole assembly if violated. A control strategy developed for such a system must avoid possible collision of the gun/turret system with these obstacles. We propose to use a MPC based control strategy, due to its inherent ability to handle constraints, for the deck clearance problem and evaluate its performance under operating conditions for a linear model of the tank. Matlab~R based MPCtoolbox is used to set up the MPC calculations for the gun/turret system. Simulations are performed to investigate and compare the performance of the controller under various deck constraint limits. It is shown that MPC is effective in addressing both the stabilization and deck clearance objectives.

关键词： Maximum Allowable Concentration control strategy Tanks belted distributed model predictive control nonlinear model predictive control Constraint model predictive control predictive control linear models Addressing assemblies Operating conditions vehicle controllers

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