scholarly journals Distributed Input-Delay Model Predictive Control of Inland Waterways

10.29007/p2cx ◽  
2018 ◽  
Author(s):  
Pau Segovia ◽  
Lala Rajaoarisoa ◽  
Fatiha Nejjari ◽  
Eric Duviella ◽  
Vicenç Puig
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategies ◽  
Current Control ◽  
Distributed Model ◽  
Centralized Control ◽  
Delay Model ◽  
Inland Waterways ◽  
Control Actions ◽  
System Partitioning

Inland waterways are large, complex systems composed of interconnected navigation reaches dedicated mainly to navigation. These reaches are generally characterized by negligible bottom slopes and large time delays. The latter requires ensuring the coordination of the current control actions and their delayed effects in the network. Centralized control strategies are often impractical to implement due to the size of the system. To overcome this issue, a distributed Model Predictive Control (MPC) approach is proposed. The system partitioning is based on a reordering of the optimality conditions matrix, and the control actions are coordinated by means of the Optimality Condition Decomposition (OCD) methodology. The case study is inspired by a real inland waterways system and shows the performance of the approach.

scholarly journals Mitigation of communication failures in distributed model predictive control strategies

2018 ◽  
Vol 12 (18) ◽  
pp. 2507-2515
Author(s):  
Wicak Ananduta ◽  
Julian Barreiro-Gomez ◽  
Carlos Ocampo-Martinez ◽  
Nicanor Quijano
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategies ◽  
Distributed Model ◽  
Distributed Model Predictive Control

scholarly journals Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4693 ◽  
Author(s):  
Pedro Gonçalves ◽  
Sérgio Cruz ◽  
André Mendes
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Performance ◽  
Control Strategies ◽  
Current Control ◽  
Torque Control ◽  
Current Harmonics ◽  
Electric Drives ◽  
Finite Control ◽  
Control Set

Recently, the control of multiphase electric drives has been a hot research topic due to the advantages of multiphase machines, namely the reduced phase ratings, improved fault tolerance and lesser torque harmonics. Finite control set model predictive control (FCS-MPC) is one of the most promising high performance control strategies due to its good dynamic behaviour and flexibility in the definition of control objectives. Although several FCS-MPC strategies have already been proposed for multiphase drives, a comparative study that assembles all these strategies in a single reference is still missing. Hence, this paper aims to provide an overview and a critical comparison of all available FCS-MPC techniques for electric drives based on six-phase machines, focusing mainly on predictive current control (PCC) and predictive torque control (PTC) strategies. The performance of an asymmetrical six-phase permanent magnet synchronous machine is compared side-by-side for a total of thirteen PCC and five PTC strategies, with the aid of simulation and experimental results. Finally, in order to determine the best and the worst performing control strategies, each strategy is evaluated according to distinct features, such as ease of implementation, minimization of current harmonics, tuning requirements, computational burden, among others.

scholarly journals Direct Phase Angle and Voltage Amplitude Model Predictive Control of a Power Converter for Microgrid Applications

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2254
Author(s):  
Thai-Thanh Nguyen ◽  
Hyeong-Jun Yoo ◽  
Hak-Man Kim ◽  
Huy Nguyen-Duc
Keyword(s):  
Model Predictive Control ◽  
Power Control ◽  
Phase Angle ◽  
Predictive Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Operation Mode ◽  
Power Converter ◽  
Current Control ◽  
Voltage Amplitude

Several control strategies of the finite control set model predictive controls (FCS-MPC) have been proposed for power converters, such as predictive current control (PCC), direct predictive power control (DPPC), and predictive voltage control (PVC). However, for microgrid (MG) applications, the control strategy of the FCS-MPC for a power converter might be changed according to the operation mode of the MG system, which results in a transient response in the system voltage or current during the mode transition. This study proposes a new control strategy of FCS-MPC for use in both islanded and grid-connected operation modes of an MG system. Considering the characteristic of a synchronous generator, a direct phase angle and voltage amplitude model predictive control (PAC) of a power converter is proposed in this study for MG applications. In the islanded mode, the system frequency is directly controlled through the phase angle of the output voltage. In the grid-connected mode, a proportional-integral (PI) regulator is used to compensate for the phase angle and voltage amplitude of the power converter for constant power control. The phase angle of the system voltage can be easily adjusted for the synchronization process of an MG system. A comparison study on the proposed PAC method and existing predictive methods is carried out to show the effectiveness of the proposed method. The feasibility of the proposed PAC strategy is evaluated in a simulation-based system by using the MATLAB/Simulink environment.

scholarly journals Design and Analysis of Model Predictive Control based Direct and Indirect Current strategy for Single Phase Shunt Active Power Filter

2018 ◽  
Vol 225 ◽  
pp. 05017
Author(s):  
Rameshkumar Kanagavel ◽  
V. Indragandhi ◽  
K Palanisamy
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Single Phase ◽  
Control Method ◽  
Control Strategies ◽  
Active Power Filter ◽  
Active Power ◽  
Current Control ◽  
Shunt Active Power Filter ◽  
Power Filter

In this paper presents a comparative analysis of two control method applied to a single phase Shunt Active Power Filter (SAPF). It is about Model Predictive Control (MPC) based Direct Current Control (DCC) and Indirect Current Control (IDCC) strategy. The performances of two current control strategies were verified through a simulation with MATLABSimulink Software. Simulation results confirmed that compared to the DCC strategy, the IDCC strategy using MPC becomes simpler and need less hardware components.

scholarly journals Energy-Saving Train Regulation for Metro Lines Using Distributed Model Predictive Control

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5483
Author(s):  
Fei Shang ◽  
Jingyuan Zhan ◽  
Yangzhou Chen
Keyword(s):  
Energy Efficiency ◽  
Service Quality ◽  
Model Predictive Control ◽  
Energy Saving ◽  
Real Time ◽  
Predictive Control ◽  
Distributed Model ◽  
Control Input ◽  
Centralized Control ◽  
Distributed Model Predictive Control

Due to environmental concerns, the energy-saving train regulation is necessary for urban metro transportation, which can improve the service quality and energy efficiency of metro lines. In contrast to most of the existing research of train regulation based on centralized control, this paper studies the energy-saving train regulation problem by utilizing distributed model predictive control (DMPC), which is motivated by the breakthrough of vehicle-based train control (VBTC) technology and the pressing real-time control demand. Firstly, we establish a distributed control framework for train regulation process assuming each train is self-organized and capable to communicate with its preceding train. Then we propose a DMPC algorithm for solving the energy-saving train regulation problem, where each train determines its control input by minimizing a constrained local cost function mainly composed of schedule deviation, headway deviation, and energy consumption. Finally, simulations on train regulation for the Beijing Yizhuang metro line are carried out to demonstrate the effectiveness of the proposed DMPC algorithm, and the results reveal that the proposed algorithm exhibits significantly improved real-time performance without deteriorating the service quality or energy efficiency compared with the centralized MPC method.

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