• Title/Summary/Keyword: MPC control

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Optimal Control of a Coarse/Fine Position Control System with Constraints (제한조건물 고려한 조미동 위치제어 시스템의 최적제어)

  • 주완규;최기상;최기흥
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.344-344
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    • 2000
  • Recently, the demand for high precision and large stroke in linear positioning systems is increasing in industry. A coarse-fine position control system composed of a linear motor and a piezoelectric actuator has such characteristics. Many optimal control laws have been applied to the position control of coarse-fine actuators but most of them did not take account into constraints. In this study, model predictive control (MPC) method with constraints is applied to the position control of the coarse-fine actuator and the performance of MPC is compared with those of conventional control laws.

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Fast FCS-MPC-Based SVPWM Method to Reduce Switching States of Multilevel Cascaded H-Bridge STATCOMs

  • Wang, Xiuqin;Zhao, Jiwen;Wang, Qunjing;Li, Guoli;Zhang, Maosong
    • Journal of Power Electronics
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    • v.19 no.1
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    • pp.244-253
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    • 2019
  • Finite control set model-predictive control (FCS-MPC) has received increasing attentions due to its outstanding dynamic performance. It is being widely used in power converters and multilevel inverters. However, FCS-MPC requires a lot of calculations, especially for multilevel-cascaded H-bridge (CHB) static synchronous compensators (STATCOMs), since it has to take account of all the feasible voltage vectors of inverters. Hence, an improved five-segment space vector pulse width modulation (SVPWM) method based on the non-orthogonal static reference frames is proposed. The proposed SVPWM method has a lower number of switching states and requires fewer computations than the conventional method. As a result, it makes FCS-MPC more efficient for multilevel cascaded H-bridge STATCOMs. The partial cost function is adopted to sequentially solve for the reference current and capacitor voltage. The proposed FCS-MPC method can reduce the calculation burden of the FCS-MPC strategy, and reduce both the switching frequency and power losses. Simulation and experimental results validate the excellent performance of the proposed method when compared with the conventional approach.

Model predictive control strategies for protection of structures during earthquakes

  • Xu, Long-He;Li, Zhong-Xian
    • Structural Engineering and Mechanics
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    • v.40 no.2
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    • pp.233-243
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    • 2011
  • This paper presents a theoretical study of a model predictive control (MPC) strategy employed in semi-active control system with magnetorheological (MR) dampers to reduce the responses of seismically excited structures. The MPC scheme is based on a prediction model of the system response to obtain the control actions by minimizing an objective function, which can compensate for the effect of time delay that occurred in real application. As an example, a 5-story building frame equipped with two 20 kN MR dampers is presented to demonstrate the performance of the proposed MPC scheme for addressing time delay and reducing the structural responses under different earthquakes, in which the predictive length l = 5 and the delayed time step d = 10, 20, 40, 60, 100 are considered. Comparison with passive-off, passive-on, and linear quadratic Gaussian (LQG) control strategy indicates that MPC scheme exhibits good control performance similar to the LQG control strategy, both have better control effectiveness than two passive control methods for most cases, and the MPC scheme used in semi-active control system show more effectiveness and robustness for addressing time delay and protecting structures during earthquakes.

Cooperative Particle Swarm Optimization-based Model Predictive Control for Multi-Robot Formation (군집 로봇 편대 제어를 위한 협력 입자 군집 최적화 알고리즘 기반 모델 예측 제어 기법)

  • Lee, Seung-Mok;Kim, Hanguen;Myung, Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.5
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    • pp.429-434
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    • 2013
  • This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

The devlepment of a MPC controller for water level control in the steam generator of a nuclear power plant (원전 증기발생기 수위제어를 위한 MPC 제어기 개발)

  • 손덕현;한진욱;이환섭;이창구
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.359-359
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    • 2000
  • Generally, level control in the steam generator of a nuclear power plant is difficulty process control, because the low power operating can lead nonminimum phase characteristics(swell and shrink phenomenon) and flow measurement are unreliable and nonlinear characteristics. This paper presents a framework for solving this problem based on the constrained linear model predictive control and introduces the design of method for the level of the controller in the entire operating power of the steam generator, and compares with conventional PI controller.

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Control of a Three-Phase Voltage Source Inverter using Model Predictive Control of Laguerre Functions

  • Cho, Uk-Rae;Cha, Wang-Cheol;Park, Joung-Ho;Shin, Ho-Jeon;Kim, Jae-Cheol
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.29 no.2
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    • pp.40-46
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    • 2015
  • This paper presents a method of controlling a three-phase VSI (Voltage Source Inverter) using MPC (Model Predictive Control) designed using Laguerre functions. It also provides a model of the three-phase VSI and its resistive-inductive load and then an overview of MPC design using Laguerre functions. The biggest challenge in using MPC is the high number of computations involved, which makes online implementation difficult. On the other hand, the LMPC (Laguerre Model Predictive Control) reduces the number of computations made and so online implementation becomes possible where traditional MPC would be unteneble. The simulation results from MATLAB are also provided.

Finite Control Set Model Predictive Current Control for a Cascaded Multilevel Inverter

  • Razia Sultana, W.;Sahoo, Sarat Kumar
    • Journal of Electrical Engineering and Technology
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    • v.11 no.6
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    • pp.1674-1683
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    • 2016
  • In this paper, a Finite Control Set Model Predictive Control (FCS-MPC) for a five level cascaded multilevel inverter (CMLI) with reduced switch topology is proposed. Five switches are used here instead of conventionally used eight switches. The main contribution of this paper is to make the MPC controller work for the reduced switch topology using only 19 voltage vectors in place of conventional 61 voltage vectors for a five level CMLI. This simplifies the execution of the MPC algorithm, paving a way for the significant reduction in the computational time. The controller makes use of the excellent ability of MPC to multitask, by adding one more objective which is to reduce the average switching frequency in addition to controlling the load current. This is especially important, since switching losses and therefore switching frequency is significant for high-power applications. The trade-off of this MPC is that the current is not as smooth as the 61 vector scheme, but well within the limits of IEEE standards. The results shown prove that this MPC works well in steady state and dynamic conditions too.

Human Papillomavirus Genotypes Associated with Mucopurulent Cervicitis and Cervical Cancer in Hangzhou, China

  • Shen, Xing-Hang;Liu, Shu-Hua
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.6
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    • pp.3603-3606
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    • 2013
  • Background: To investigate the infection status and predominant genotype distribution of human papillomavirus (HPV) infection among Chinese patients with mucopurulent cervicitis (MPC) or cervical cancer (CC) in Hangzhou. Methods: Initially, 217 cases of healthy cervix controls (n=50), acute MPC (n=89), and CC (n=78) were included; samples were collected between January 1, 2010, and January 30, 2013. Cervical specimens were screened for HPV using a nested polymerase chain reaction assay and DNA sequencing. Results: Overall prevalence of HPV infection was 16.7% in the control group, 51.9% in the MPC group, and 84.4% in the CC group. The predominant genotype detected in all 3 groups was the oncogenic variant HPV 16 (55.8%, 17.3%, and 6.3% in the CC, MPC and control specimens, respectively), HPV58 was the second most predominant HPV type in CC (9.1%), MPC (8.6%), and control group (4.2%). Most or all of the genotypes were oncogenic in the three groups. Conclusions: Infection with HPV was found to be prevalent among Chinese women with MPC or CC and oncogenic variants were in the majority. Therefore, peoples who suffered MPC with HPV DNA positive should be regularly followed-up, for prevention and early treatment of cervical cancer.

Stability and Performance Investigations of Model Predictive Controlled Active-Front-End (AFE) Rectifiers for Energy Storage Systems

  • Akter, Md. Parvez;Mekhilef, Saad;Tan, Nadia Mei Lin;Akagi, Hirofumi
    • Journal of Power Electronics
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    • v.15 no.1
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    • pp.202-215
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    • 2015
  • This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

Design and Experimental Validation of a Digital Predictive Controller for Variable-Speed Wind Turbine Systems

  • Babes, Badreddine;Rahmani, Lazhar;Chaoui, Abdelmadjid;Hamouda, Noureddine
    • Journal of Power Electronics
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    • v.17 no.1
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    • pp.232-241
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    • 2017
  • Advanced control algorithms must be used to make wind power generation truly cost effective and reliable. In this study, we develop a new and simple control scheme that employs model predictive control (MPC), which is used in permanent magnet synchronous generators and grid-connected inverters. The proposed control law is based on two points, namely, MPC-based torque-current control loop is used for the generator-side converter to reach the maximum power point of the wind turbine, and MPC-based direct power control loop is used for the grid-side converter to satisfy the grid code and help improve system stability. Moreover, a simple prediction scheme is developed for the direct-drive wind energy conversion system (WECS) to reduce the computation burden for real-time applications. A small-scale WECS laboratory prototype is built and evaluated to verify the validity of the developed control methods. Acceptable results are obtained from the real-time implementation of the proposed MPC methods for WECS.