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

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MPC based State Observer and its application for system with input-output disturbances

MPC based State Observer and its application for system with...

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IEEE International Conference on Power and Energy Systems (ICPES)

作者： S. Shadab D. Pardeshi S. Mohite S. Bhil EED VJTI Mumbai India

ISBN: (数字)9781728126586

ISBN: (纸本)9781728126593

The progression of current advancements and innovative development of power electronics has prompted the extensive utilization of Buck-Boost converters in battery management system, automatic power supplies and power amplifiers. The control objective is to track the output voltage under varying load and varying reference voltage. The nonlinear states of the converter are controlled by a systematic linearization strategy. The High Gain Observer (HGO) is formulated to estimate the output voltage and load current and these estimated values are fed forward to the model predictive controller (MPC). The convergence of load current trajectories to reference current trajectories within a finite time is ensured by MPC. Output voltage tracking with the reference voltage is achieved by duty ratio generated by the inner control loop. The viability of implementation of the proposed estimator-controller combination are carried out on MATLAB Simulink.

关键词： Buck-Boost converter High Gain Observer model predictive control boost converters output voltage Maximum Allowable Concentration voltage reference Power electronics Observers high gain load current model predictive control predictive control distributed model predictive control nonlinear model predictive control Battery management systems variable amplitude loading stacking factor

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Hierarchical distributed MPC for Longitudinal and Lateral Vehicle Platoon control with Collision Avoidance

Hierarchical Distributed MPC for Longitudinal and Lateral Ve...

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第42届中国控制会议

作者： Hankun Liu Zhiwen Qiang Li Dai Boli Chen Yuanqing Xia Beijing Institute of Technology University College London

This paper proposes a hierarchical distributed model predictive control(MPC) method for vehicle platoon control in both longitudinal and lateral directions. In the upper layer, a novel path-planning module and a trajectory-fusion module are utilized to compute a smooth reference trajectory for each follower. In the lower layer, the longitudinal and lateral distributed model predictive controllers are decoupled to control the velocity and steering respectively. To ensure safety and reduce the computation burden, the constraints to avoid collision are reformulated by using the strong duality theory. A simulation is conducted to demonstrate the effectiveness of the proposed control algorithm in maintaining platoon formation and ensuring the safety of the platoon.

关键词： distributed model predictive control Longitudinal and lateral control Vehicle platoon Collision avoidance constraints

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Multi-objective optimal control of stochastic hybrid systems

Multi-objective optimal control of stochastic hybrid systems

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IEEE Annual Conference on Decision and control

作者： Sean Summers John Lygeros Department of Electrical Engineering ETH Zurich

ISBN: (纸本)9781467320658

We present a dynamic programming based solution to a stochastic optimal control problem for a controlled discrete-time stochastic hybrid system. A general summultiplicative cost function is introduced along with a corresponding dynamic recursion that quantifies the weighted costs of achieving multiple (possibly competing) objectives relevant to the theory of stochastic verification and stochastic model predictive control. It is shown that a valuable collection of multi-objective stochastic optimal control problems can be expressed in the form of the presented general sum-multiplicative cost function. A case study in the early retirement problem (equivalently the reinsurance problem) is presented.

关键词： hybrid systems stochastic optimal control Cost functions Stochastic multi-objective control Optimal control distributed model predictive control nonlinear model predictive control Early retirement

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model predictive control applied to a river system with two reaches

Model Predictive Control applied to a river system with two ...

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IEEE Annual Conference on Decision and control

作者： Maarten Breckpot Oscar Mauricio Agudelo Bart De Moor Department of Electrical Engineering SCD KU Leuven

ISBN: (纸本)9781467320658

Many control strategies can be found in literature for controlling a river system. Most of these methods focus on set-point control such that the most upstream or downstream part of each reach tracks a certain reference trajectory while minimizing the effect of disturbances. However many of the control techniques suitable for set-point control cannot be used at the same time for preventing a river from flooding when large disturbances take place. In this paper we show that model predictive control can be used for set-point control and flood control of a river system consisting of two reaches and one gate. For this we use a linearized version of the Saint-Venant equations with special attention to the gate dynamics.

关键词： set point control River systems model predictive control predictive control rivers OR gates distributed model predictive control nonlinear model predictive control Flood control

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Comparison of optimized pulse patterns with Direct model predictive control using co-simulation

Comparison of optimized pulse patterns with Direct Model Pre...

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8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016)

作者： Christoph Schulte Klaus Peter Michael Leuer Joachim Böcker Universitat Paderborn Paderborn Nordrhein-Westfalen DE

ISBN: (纸本)9781510825666

Accurate simulation of electric drives has always been desirable, as it allows the machine designer a deeper insight into the whole design. This publication presents a comparison of two different control approaches. To maximize the results' accuracy, no reduced-order models of the control structure or of the motor model are being used. The comparison includes a PI-controller with optimized pulse patterns and a Direct model predictive control. As a benchmark the current response and the magnet loss are compared. The comparison of both control strategies shows that the model predictive control offers high dynamics buts leading to higher magnet loss compared with the optimized pulse patterns. The simulated magnet loss values of the optimized pulse patterns correlates well with the results of the analytical approach.

关键词： Co-simulation Finite-Element-Analysis model predictive control Predetermined pulse patterns Magnet loss pulse pattern model predictive control predictive control Finite element method distributed model predictive control nonlinear model predictive control motor model control Architecture PI control electric drives

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distributed predictive control method based on neighborhood optimization for high-speed electric multiple unit

Distributed predictive control method based on neighborhood ...

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第26届中国过程控制会议（CPCC2015）

作者： Li Zhongqi Yang Hui School of Electrical and Electronic Engineering East China Jiaotong University Key Laboratory of Advanced Control & Optimization of Jiangxi Province

This paper proposes a new predictive control scheme for the high-speed electric multiple unit(EMU), by establishing multiple distributed state-space model for each power unit based on the subspace model identification method, according to the structure characteristics of EMU composed by several coupled power units, and the actual data and the traction/brake characteristic curve. Each power unit is designed by the distributed predictive control method and the neighborhood optimization strategy is used to coordinate such power units. Such a method can take advantage of each power unit output information and status information of the neighborhood in the optimization process, consider the performance index of the neighborhood fully, improve the global control performance of the EMU and reduce the online computation compared to the centralized control mode. The convergence and the stability conditions are discussed in this paper. Simulation results based on the actual CRH380 A operation data show the effectiveness of the proposed method.

关键词： High-speed electric multiple unit Power unit Neighborhood optimization distributed model predictive control

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Regulation Service for the Short-Term Management of Renewable Energy Microgrids with Hybrid Storage using model predictive control

Regulation Service for the Short-Term Management of Renewabl...

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Annual Conference of the IEEE Industrial Electronics Society

作者： F. Garcia C. Bordons Departamento de Ingenieria de Sistemas y Automatica Escuela Superior de Ingenieros. Universidad de Sevilla

ISBN: (纸本)9781479902255

The electricity market rules determine the energy price in the day-ahead market, matching offers from generators to bids from consumers to develop a classic supply and demand equilibrium price, usually on an hourly interval. The unpredictability of renewable energy joined to the penalty deviations used in the regulation market make it difficult for clean energy to play an important role in the system. The use of Energy Storage Systems (ESS) integrated in a microgrid (μG) structure with renewable energy systems using two level scheduling, long-term (40 hours) and short-term (1 hour) appears as a solution to minimize the penalty deviations. In this paper, the short-term regulation service optimization linked to the long-term economical dispatch of a grid-connected renewable energy μG is addressed. The μG includes hybrid energy storage composed of hydrogen storage (HESS), battery storage (BESS) and ultracapacitor storage (UESS). It is managed with model predictive control (MPC) in order to maximize the economical benefit minimizing the degradation causes of each storage system. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled with the framework of mixed logic dynamic (MLD). Taking into account the presence of integer variables, the MPC problem is solved using MIQP (Mixed Integer Quadratic Programming).

关键词： Hybrid systems Interfacing and control of energy storage technology distributed and Micro- and off-grid generation Hydrogen hybrid systems Renewable energy Cache Memory System Hydrogen model predictive control predictive control Energy costs quadratic programming Clean energy ENERGY SYSTEMS distributed model predictive control nonlinear model predictive control Standing Orders Regulation (biology) Maximum Allowable Concentration

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Distribution Systems Reliability and Economic Improvement with Different Electric Energy Storage control Strategies

Distribution Systems Reliability and Economic Improvement wi...

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IEEE Power and Energy Society General Meeting

作者： Yixing Xu Chanan Singh Texas A&M University

ISBN: (纸本)9781457710001

With the rapid development of electric energy storage (EES) technologies, there is a growing interest in integrating these into distribution systems to improve their reliability and economy. Different control strategies of EES have corresponding reliability and economic impacts on the system. In this paper, the reliability and economy of radial distribution system integrated with EES are assessed. The control strategy of utilizing EES as a standby backup energy resource is analyzed. This standby backup control strategy improves system reliability the most but falls short on economy improvement. A novel MPC-based control strategy is presented, which can maximize distribution system economy but could not improve reliability as much as the standby backup control strategy. A hybrid control strategy of balancing the reliability and economy improvement by combining the standby backup control strategy and MPC-based control strategy is presented. The reliability and economic analysis of distribution system integrated with EES using proposed control strategies illustrates the effectiveness of the proposed method. It also illustrates that even with the same EES integrated into the distribution system, different control strategies have very different reliability and economic impact on the system. In order to accurately assess the impact of the implemented control strategies, sequential Monte Carlo Simulation is used and implemented EES control operations are included in the simulation.

关键词： Distribution system Reliability analysis Economy analysis Electric energy storage model predictive control dispensing system control strategy electric energy storage Reliability analysis Economy US ENERGY EXTENSION SERVICE distributed model predictive control nonlinear model predictive control Economic impact

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Performance Comparision of Kalman Filter and RLS models in MPC Applications

Performance Comparision of Kalman Filter and RLS Models in M...

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International Conference on Electrical, control and Instrumentation Engineering (ICECIE)

作者： Mawia El-Gazzar Awad Shamekh Ali Altowati University of Benghazi Benghazi Libya School of Technology and Innovations Telecommunications Engineering University of Vaasa Vaasa Finland

ISBN: (纸本)9781728139401

This paper considers a comparison between the Kalman Filter (KF) and the Recursive Least Squares (RLS) models in the design of model predictive control (MPC). The assessment is validated through two industrial applications; a two-coupled tank and binary distillation column systems. The study has conducted several simulation scenarios using Matlab/Simulink software. Linear models are identified for the controlled systems where the input and output variables are subjected to non-stationary measurement of noise. In the first application, the Extended Kalman Filter (EKF) is utilized to provide a state space suboptimal model for the two-coupled tank system. The EKF is suggested as this process is characterized as a nonlinear system. The estimated model is then incorporated with the MPC control law to drive the process outputs to follow their set point trajectories. Similarly, the RLS algorithm was exploited to identify the parameters of multi-input single-output relationships for the aforementioned system. The similar policy was also implemented for the second application, which undertakes the binary distillation column. This system is classified as a linear process in this research, therefore the standard KF is utilized with application. The performance of the designed MPC scenarios, based on the two identification approaches, are evaluated by means of the Integral Squares Error (ISE) performance index.

关键词： Extended Kalman Filter Recursive Least Square model predictive control Two-Coupled Tank Binary Distillation Column recursive least squares Extended Kalman filters Restless Legs Syndrome Maximum Allowable Concentration model predictive control predictive control control law Distillation columns distributed model predictive control nonlinear model predictive control Kalman filters

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Laguerre Function based model predictive control for Multiple Product Inventory System

Laguerre Function based Model Predictive Control for Multipl...

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Emerging Trends in Communication, control and Computing (ICONC3), International Conference on

作者： Akansha Jain Rajashree Taparia Rajasthan Technical University Kota Rajasthan

ISBN: (数字)9781728114200

ISBN: (纸本)9781728114217

This paper describes model predictive based control for a multiple product inventory system. Inventory systems are designed for replenishment orders to fill the stock. The orders for the products are issued such that the demand for the product is met and a desired stock is maintained. In case of inventory systems with multiple products the same objectives are desired for individual products. The demand for the products is unknown prior. The system dynamics is not affected by the demand for the products but affected by the supply and the arriving orders. model predictive control has the ability to work in constrained environment of states as well as control input and the number of parameters are reduced by using Laguerre model predictive control in the control law. control law for replenishment orders is derived and simulations on a two product inventory system are shown for validation.

关键词： multiple product inventory system lead-time model predictive control Laguerre functions constraints Laguerre functions LEAD TIME model predictive control predictive control distributed model predictive control nonlinear model predictive control inventories control input

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