Speed Control of an Asynchronous Motor Using PID Neural Network

Maraba, V. Ayhan; Kuzuncuoglu, A. Emin

doi:10.24846/v20i3y201101

Cited by 4 publications

(4 citation statements)

References 2 publications

(7 reference statements)

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“…According to the Hebb learning rule [17] and avoiding local minima [18], an improved algorithm for adjusting the weights is proposed and deduced as follows…”

Section: Neural Network Pidmentioning

confidence: 99%

NNPID-based Stator Voltage Oriented Vector Control for DFIG based Wind Turbine Systems

Li¹,

Wang²,

Yang³

et al. 2014

SIC

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Doubly fed induction generators are widely adopted for the wind turbine systems since it is cheap and reliable. Based on the traditional stator voltage oriented vector control method, the performance of the proposed vector control is largely influenced by the variations of the DFIG parameters. And the classical PID algorithm cannot achieve the maximum power point tracking (MPPT) in time (owing to the transient wind). Hence, in this paper, to eliminate parameters variations on the power output and capture the MPPT rapidly, we propose a stator voltage oriented vector control which is based on a Neural Network PID (NNPID) technology. The weights which are being similar to the PID coefficients are adapted by Hebb rule to decrease the power error online according to the error gradient descent method, while the classical PID coefficients will be a constant. The effectiveness of the proposed method is demonstrated by corresponding simulation results: even in the case of wind mutation change, the proposed NNPID can track the variation of the wind energy, and robust to the DFIG parameters variations.

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“…According to the Hebb learning rule [17] and avoiding local minima [18], an improved algorithm for adjusting the weights is proposed and deduced as follows…”

Section: Neural Network Pidmentioning

confidence: 99%

NNPID-based Stator Voltage Oriented Vector Control for DFIG based Wind Turbine Systems

Li¹,

Wang²,

Yang³

et al. 2014

SIC

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“…One of the mechatronics subsystems that is highly demanded by the industry is the three-phase inverter-motor system, which is part of the final control element and has been extensively researched. [1]- [3] Most of the research in this area focuses on the design of new algorithms for diagnosing or reconfiguring the failure [4] and analysis of new tolerant schemes for the inverter-motor system under the material redundancy approach . [1], [2], [5] Other important areas that still require more research are the importance of early detection of the failure in the device´s power to prevent its spread, and the right timing for the replacement of the damaged element thus reducing the tracking in the control error.…”

Section: Introductionmentioning

confidence: 99%

IGBT fault diagnosis using adaptive thresholds during the turn-on transient

Blanco

Vazquez-Perez

Hernández-González

et al. 2013

2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)

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Φ Abstract --This paper presents the design of an electronic fault detection circuit in the insulated gate bipolar transistor (IGBT) based on the exclusive measurement of the gate signal during the turn-on transient. In order to increase the effectiveness of the detection and to tolerate the variations of input to system, adaptable thresholds have been added to the circuit. There are three important aspects in this research, specifically: 1 -Early detection, since the evaluation is realized during the turn-on transient; 2 -Reducing false alarms, because the variations of input to the system are considered; 3 -A realistic design, since the components used are commercially available, and the IGBT model used is the standard for PSpice software which has already been widely validated in the literature.The authors wish to acknowledge gratefully to CONACYT-CVU: 362028 and UNACAR by financial support. M. A Rodríguez-Blanco, A. Vázquez-Pérez, A. Pech-Carbonel, M. May-Alarcón are with

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“…The compression system model Notations are defined in Table 1. Inducer perimeter radius 0.0395m r 2 Impeller perimeter radius 0.0565m…”

Section: Modeling Of the Recycle Compression Systemmentioning

confidence: 99%

“…This approach is known as artificial intelligent active surge control. In recent years intelligent active surge control has been an active area of research as in [1,2,3,4] have been focused on modelling and control. Active surge control has showed the ability to extend the operating range significantly [3,4].…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Control of the Recycle Compression System

Boushaki¹,

Chetate²,

Zamoum³

2014

SIC

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This paper presents results from an investigation on a nonlinear compressor control. The useful range of operation of turbo compressors is limited by choking at high rate flows and by the onset of instability known as surge at low rate flows. Traditionally, this instability has been avoided by using control systems that prevent the operating point of the compressor to enter in the unstable region. It is not efficient to apply classical controllers, such as simple P, PI and PID when the parameters of compression system change frequently. The aim of our work is to design and simulate an intelligent controller. A simulation part is clearly presented with the advantages of the intelligent system.

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Speed Control of an Asynchronous Motor Using PID Neural Network

Cited by 4 publications

References 2 publications

NNPID-based Stator Voltage Oriented Vector Control for DFIG based Wind Turbine Systems

NNPID-based Stator Voltage Oriented Vector Control for DFIG based Wind Turbine Systems

IGBT fault diagnosis using adaptive thresholds during the turn-on transient

Artificial Neural Network Control of the Recycle Compression System

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