• Title, Summary, Keyword: predictive method

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The Design of Trajectory Controller using Neural Networks Simulating Predictive Control Method for Mobile Robot (이동로봇의 예측제어방법을 모사한 신경회로망 궤적제어기 설계)

  • Park, Jin-Hyun;Lee, Tae-Hwan;Bae, Jun-Kyung
    • Journal of the Korean Society of Mechanical Technology
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    • v.19 no.4
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    • pp.538-544
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    • 2017
  • The predictive control system using model-based predictive control is a very effective way to optimize the present inputs considering the states and future errors of the reference trajectory, but it has a drawback in that a control input matrix must be repeatedly calculated with a long calculation time at every sampling for minimizing future errors in a predictive interval. In this study, we applied the neural network simulating the predictive control method for the trajectory tracking control of the mobile robot to reduce complex control method and computation time which are the disadvantage of predictive control. In addition, the neural network showed excellent performance by the generalization even for a different reference trajectory. Therefore, The controller is designed by modeling the model-based predictive control gains for the reference trajectory using a neural networks. Through the computer simulation, the proposed control method showed better performance than the general predictive control method.

Pseudospectral Model Predictive Control for Exo-atmospheric Guidance

  • Rahman, Tawfiqur;Zhou, Hao;Yang, Liang;Chen, Wanchun
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.1
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    • pp.64-76
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    • 2015
  • This paper suggests applying pseudospectral model predictive method for exo-atmospheric guidance. The method is a fusion of pseudospectral law and model predictive control, in which a two point boundary value problem is formulated using model predictive approach and solved by applying pseudospectral law. In this work, the method is applied to exo-atmospheric guidance with specific target requirement. The existing exo-atmospheric guidance methods suffice general requirements for guidance, but cannot ensure specific target constraints; whereas, the presented method is able to do so. The proposed guidance law is assessed through simulation of perturbed cases, and the tests suggest that the method is able to operate semi-autonomously under control and thrust vector perturbations.

A Model Predictive Control Method to Reduce Common-Mode Voltage for Voltage Source Inverters

  • Vu, Huu-Cong;Lee, Hong-Hee
    • Proceedings of the KIPE Conference
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    • pp.209-210
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    • 2015
  • This paper presents a new model predictive control method without the effect of a weighting factor in order to reduce common-mode voltage (CMV) for a three-phase voltage source inverter (VSI). By utilizing two active states with same dwell time during a sampling period instead of one state used in conventional method, the proposed method can reduce the CMV of VSI without the weighting factor. Simulation is carried out to verify the effectiveness of the proposed predictive control method with the aid of PSIM software.

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Imposed Weighting Factor Optimization Method for Torque Ripple Reduction of IM Fed by Indirect Matrix Converter with Predictive Control Algorithm

  • Uddin, Muslem;Mekhilef, Saad;Rivera, Marco;Rodriguez, Jose
    • Journal of Electrical Engineering and Technology
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    • v.10 no.1
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    • pp.227-242
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    • 2015
  • This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

A Novel Predictive Digital Controlled Sensorless PFC Converter under the Boundary Conduction Mode

  • Wang, Jizhe;Maruta, Hidenori;Matsunaga, Motoshi;Kurokawa, Fujio
    • Journal of Power Electronics
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    • v.17 no.1
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    • pp.1-10
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    • 2017
  • This paper presents a novel predictive digital control method for boundary conduction mode PFC converters without the need for detecting the inductor current. In the proposed method, the inductor current is predicted by analytical equations instead of being detected by a sensing-resistor. The predicted zero-crossing point of the inductor current is determined by the values of the input voltage, output voltage and predicted inductor current. Importantly, the prediction of zero-crossing point is achieved in just a single switching cycle. Therefore, the errors in predictive calculation caused by parameter variations can be compensated. The prediction of the zero-crossing point with the proposed method has been shown to have good accuracy. The proposed method also shows high stability towards variations in both the inductance and output power. Experimental results demonstrate the effectiveness of the proposed predictive digital control method for PFC converters.

Actual Energy Consumption Analysis of Temperature Control Strategies for Secondary Side Hot Water District Heating System with an Inverter (인버터시스템 적용 지역난방 시스템의 2차측 공급수 온도 제어방안에 따른 에너지사용량 실증 비교)

  • Cho, Sung-Hwan;Hong, Seong-Ki
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.27 no.4
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    • pp.179-186
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    • 2015
  • In this study, the actual energy consumption of the secondary side District Heating System (DHS) with different hot water supply temperature control methods is compared. The two methods are Outdoor Temperature Reset Control and Outdoor Temperature Predictive Control. While Outdoor Temperature Reset Control has been widely used for energy savings of the secondary side system, the results show that the Outdoor Temperature Predictive Control method saves more energy. In general, the Outdoor Temperature Predictive Control method lowers the supply temperature of hot water, and it reduces standby losses and increases the overall heat transfer value of heated spaces due to more flow into the space. During actual energy consumption monitoring, the Outdoor Temperature predictive Control method saves about 6.6% of energy when compared to the Outdoor Temperature Reset Control method. Also, it is found that at partial load condition, such as during daytime, the fluctuation of hot water supply temperature with Outdoor Temperature Reset Control is more severe than that with Outdoor Temperature Predictive Control. Thus, it proves that Outdoor Temperature Predictive Control is more stable even at partial load conditions.

Improved Deadbeat Current Controller with a Repetitive-Control-Based Observer for PWM Rectifiers

  • Gao, Jilei;Zheng, Trillion Q.;Lin, Fei
    • Journal of Power Electronics
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    • v.11 no.1
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    • pp.64-73
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    • 2011
  • The stability of PWM rectifiers with a deadbeat current controller is seriously influenced by computation time delays and low-pass filters inserted into the current-sampling circuit. Predictive current control is often adopted to solve this problem. However, grid current predictive precision is affected by many factors such as grid voltage estimated errors, plant model mismatches, dead time and so on. In addition, the predictive current error aggravates the grid current distortion. To improve the grid current predictive precision, an improved deadbeat current controller with a repetitive-control-based observer to predict the grid current is proposed in this paper. The design principle of the proposed observer is given and its stability is discussed. The predictive performance of the observer is also analyzed in the frequency domain. It is shown that the grid predictive error can be decreased with the proposed method in the related bode diagrams. Experimental results show that the proposed method can minimize the current predictive error, improve the current loop robustness and reduce the grid current THD of PWM rectifiers.

A semiparametric method to measure predictive accuracy of covariates for doubly censored survival outcomes

  • Han, Seungbong;Lee, JungBok
    • Communications for Statistical Applications and Methods
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    • v.23 no.4
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    • pp.343-353
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    • 2016
  • In doubly-censored data, an originating event time and a terminating event time are interval-censored. In certain analyses of such data, a researcher might be interested in the elapsed time between the originating and terminating events as well as regression modeling with risk factors. Therefore, in this study, we introduce a model evaluation method to measure the predictive ability of a model based on negative predictive values. We use a semiparametric estimate of the predictive accuracy to provide a simple and flexible method for model evaluation of doubly-censored survival outcomes. Additionally, we used simulation studies and tested data from a prostate cancer trial to illustrate the practical advantages of our approach. We believe that this method could be widely used to build prediction models or nomograms.

Block-wise Adaptive Predictive PLS using Block-wise Data Extraction (데이터 추출 과정을 적용한 Block-wise Adaptive Predictive PLS)

  • Kim Sung-Young;Chung Chang-Bock;Choi Soo-Hyoung;Lee Bom-Sock
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.7
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    • pp.706-712
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    • 2006
  • Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

Predictive controller using weighted input (입력 가중치를 이용한 예측제어)

  • 나상섭;신세희;어영구
    • 제어로봇시스템학회:학술대회논문집
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    • pp.343-347
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    • 1989
  • In this paper, predictive control method using actual applied input which is the weighted summation of past inputs is presented. In conventional predictive control methods, a set of control inputs is computed and in these only the first element is applied to the process at each time instant. But this predictive control method based on conventional methods considers all computed control inputs. Consequently, the characteristic of response and the reliability of the control scheme in the case of imperfact model are improved.

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