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A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction motor drives

A. CHITRA,S. HIMAVATHI

Frontiers in Energy 2015, Volume 9, Issue 1,   Pages 22-30 doi: 10.1007/s11708-014-0339-1

Abstract: Online estimation of rotor resistance is essential for high performance vector controlled drives. In this paper, a novel modified neural algorithm has been identified for the online estimation of rotor resistance. Neural based estimators are now receiving active consideration as they have a number of advantages over conventional techniques. The training algorithm of the neural network determines its learning speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. In this paper, the neural estimator has been studied with conventional and proposed learning algorithms. The sensitivity of the rotor resistance change has been tested for a wide range of variation from -50% to+50% on the stability of the drive system with and without estimator. It is quiet appealing to settle with optimal estimation time and error for the viable realization. The study is conducted extensively for estimation and tracking. The proposed learning algorithm is found to exhibit good estimation and tracking capabilities. Besides, it reduces computational complexity and, hence, more feasible for practical digital implementation.

Keywords： neural networks     back propagation (BP)     rotor resistance estimators     vector control     induction motor    

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A pre-compensation method of the systematic contouring error for repetitive command paths

D. L. ZHANG,Y. H. CHEN,Y. P. CHEN

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 4,   Pages 367-372 doi: 10.1007/s11465-015-0367-5

Abstract: To obtain the pre-compensation value with better accuracy, this paper proposes the use of a back propagation

Keywords： contouring error     pre-compensation     motion control system     back propagation (BP) neural network    

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hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a backpropagation neural network

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1697-x

Abstract:

● Titanium-based flow-through electrode achieved high Cr(VI) reduction efficiency.

Keywords： Flow-through electrode     Hexavalent chromium     Heavy metals     Neural network     Artificial intelligence    

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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

Frontiers in Energy 2016, Volume 10, Issue 1,   Pages 105-113 doi: 10.1007/s11708-016-0393-y

Abstract: This paper proposes the day-ahead electricity price forecasting using the artificial neural networks (ANN) and weighted least square (WLS) technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices (LMP) in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach proposed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland (PJM) interconnection is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.

Keywords： day-ahead electricity markets     price forecasting     load forecasting     artificial neural networks     load serving entities    

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Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 474-485 doi: 10.1631/FITEE.1400295

Abstract: Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmesPosture of the participant plays a vital role in accurate measurement of BP.Guidelines on measurement of BP contain recommendations on the position of the back of the participantsby advising that they should sit with supported back to avoid spuriously high readings.reactivity to an unsupported back in normotensive and hypertensive participants.

Keywords： Blood pressure (BP)     Principal component analysis (PCA)     Forward stepwise regression     Artificial neural    

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Discussion on back-to-back two-stage centrifugal compressor compact design techniques

Lei HUO, Huoxing LIU

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 4,   Pages 390-400 doi: 10.1007/s11465-013-0278-2

Abstract:

Design a small flow back-to-back two-stage centrifugal compressor in the aviation turbocharger, theTherefore, the stationary part of the back-to-back two-stage centrifugal compressor should pay full attention

Keywords： back-to-back     two-stage     centrifugal compressor     design     Internal flow    

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Study on the Purification of Wastewater in the Constructed Wetland Based on GA－BP Network

Huang Juan,Wang Shihe,Luo Weiguo,Qian Weiyi ,Yan Lu

Strategic Study of CAE 2007, Volume 9, Issue 2,   Pages 79-83

Abstract: Optimized GA-BP network was established to simulate orthogonal test of wetland system.

Keywords： constructed wetlands     wastewater purification     GA-BP network     orthogonal test    

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Choosing configurations of transmission line tower grounding by back flashover probability value

Dmitry KUKLIN

Frontiers in Energy 2016, Volume 10, Issue 2,   Pages 213-226 doi: 10.1007/s11708-016-0398-6

Abstract: The probability of back flashover, which provides both qualitative and quantitative estimate of the groundingDifferent approaches are examined for identifying the back flashover probability, as not only amplitudesIt is found that lightning current waveform can greatly influence calculated back flashover probability

Keywords： grounding     transmission line tower     back flashover probability     FDTD method    

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Research on the Forecast of the BP Neural Network Based on the Orthogonal Test

Cai Anhui,Liu Yonggang,Sun Guoxiong

Strategic Study of CAE 2003, Volume 5, Issue 7,   Pages 67-71

Abstract:

The strategy for forecasting the BP neural network was researched on the basis of the training-studyingwhose factors were the same as that of the self-contained orthogonal sample could be forecast in the BP

Keywords： BP neural network     orthogonal test     strategy     design-test approach     sample collection    

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An Improved BP Algorithm Applying to Inverse Kinematics Problems of Robot Manipulator

Wu Aiguo,Hao Runsheng

Strategic Study of CAE 2005, Volume 7, Issue 7,   Pages 34-38

Abstract: paper, an algorithm in which active function is improved is proposed through analyzing the conventional BPnetworks are used to establish the inverse kinematics models for robot manipulator by this improved BPand improves the inverse kinematics solutions for robot manipulator as compared to the conventional BP

Keywords： neural networks     BP algorithm     active function     robot manipulator     inverse kinematics    

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DFIG sliding mode control fed by back-to-back PWM converter with DC-link voltage control for variable

Youcef BEKAKRA,Djilani BEN ATTOUS

Frontiers in Energy 2014, Volume 8, Issue 3,   Pages 345-354 doi: 10.1007/s11708-014-0330-x

Abstract: control of doubly fed induction generator (DFIG) with the rotor connected to the electric grid through a back-to-backA proportional-integral-(PI) controller is used to keep the DC-link voltage constant for a back-to-back

Keywords： doubly fed induction generator (DFIG)     wind turbine     back-to-back pulse width modulation (PWM)     DC-link    

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The Safe and Quick Long-Distance Transmission MethodBased on BP Neural Net for Engineering Graphics Data

Qin Wei,Qin Shuyu

Strategic Study of CAE 2007, Volume 9, Issue 1,   Pages 49-52

Abstract: is built and data code compression and data encryption are put in practice at the same time by using BP

Keywords： neural net     BP algorithm     correlation     encrypt     speed transmission     graphics data    

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Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

Frontiers in Energy 2014, Volume 8, Issue 4,   Pages 459-463 doi: 10.1007/s11708-014-0335-5

Abstract: a 1000 MW ultra-supercritical (USC) unit, the turbine cold-end system, was performed utilizing the backpropagation (BP) neural network method with genetic algorithm (GA) optimization analysis.

Keywords： optimization     turbine     cold-end system     BP neural network     genetic algorithm    

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Renewable synthetic fuel: turning carbon dioxide back into fuel

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 145-149 doi: 10.1007/s11708-022-0828-6

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Research on Nonlinear Combination Forecasting Approach Based on BP-AGA

Wang Shuo,Zhang Youfu,Jin Juliang

Strategic Study of CAE 2005, Volume 7, Issue 4,   Pages 83-87

Abstract: AGA was used to optimize the network parameters as BP approach was slow with training network.Optimization results of AGA were taken as original values of BP approach, the network was trained withBP approach.Network convergence rate was increased with running BP approach and AGA alternately.

Keywords： neural network     accelerating genetic algorithm     nonlinear combination forecasting     forecasting precision    

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Title Author Date Type Operation

A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction motor drives

A. CHITRA,S. HIMAVATHI

Journal Article

A pre-compensation method of the systematic contouring error for repetitive command paths

D. L. ZHANG,Y. H. CHEN,Y. P. CHEN

Journal Article

hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a backpropagation neural network

Journal Article

Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

Journal Article

Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric

Gurmanik KAUR,Ajat Shatru ARORA,Vijender Kumar JAIN

Journal Article

Discussion on back-to-back two-stage centrifugal compressor compact design techniques

Lei HUO, Huoxing LIU

Journal Article

Study on the Purification of Wastewater in the Constructed Wetland Based on GA－BP Network

Huang Juan,Wang Shihe,Luo Weiguo,Qian Weiyi ,Yan Lu

Journal Article

Choosing configurations of transmission line tower grounding by back flashover probability value

Dmitry KUKLIN

Journal Article

Research on the Forecast of the BP Neural Network Based on the Orthogonal Test

Cai Anhui,Liu Yonggang,Sun Guoxiong

Journal Article

An Improved BP Algorithm Applying to Inverse Kinematics Problems of Robot Manipulator

Wu Aiguo,Hao Runsheng

Journal Article

DFIG sliding mode control fed by back-to-back PWM converter with DC-link voltage control for variable

Youcef BEKAKRA,Djilani BEN ATTOUS

Journal Article

The Safe and Quick Long-Distance Transmission MethodBased on BP Neural Net for Engineering Graphics Data

Qin Wei,Qin Shuyu

Journal Article

Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

Journal Article

Renewable synthetic fuel: turning carbon dioxide back into fuel

Journal Article

Research on Nonlinear Combination Forecasting Approach Based on BP-AGA

Wang Shuo,Zhang Youfu,Jin Juliang

Journal Article