Multiple-Loop Digital Control Method for a 400-Hz Inverter System Based on Phase Feedback

Li, Chen; Ji, Shiming; Tan, Dapeng

doi:10.1109/tpel.2012.2188043

Cited by 53 publications

(46 citation statements)

References 25 publications

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“…As mentioned above, ANNs have the capabilities of improved learning, associative memory, and parallel processing, and they are hence widely applied in the areas of automatic control [28][29][30], signal processing [31][32][33], and pattern recognition [34][35][36]. The neurons of ANNs are connected by weights and thresholds, and adaptive computing is used to preprocess external input information through the ANNs' nonlinear mapping ability until the output meets the expected values.…”

Section: Sa-ann-based Cognition Mechanismmentioning

confidence: 99%

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

Chen

Tan

2018

Complexity

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Artificial neural networks (ANNs) are the important approaches for researching human cognition process. However, current ANNsbased cognition methods cannot address the problems of complex information understanding and fault-tolerant learning. Here we present a modeling method for cognition mechanism based on a simulated annealing-artificial neural network (SA-ANN). Firstly, the relationship between SA processing procedure and cognition knowledge evolution is analyzed, and a SA-ANN-based inference model is set up. Then, based on the inference model, a Powell SA with combinatorial optimization (PSACO) algorithm is proposed to improve the clustering efficiency and recognition accuracy for the cognition process. Finally, three groups of numerical instances for knowledge clustering are provided, and three comparative experiments are performed by self-developed cognition software. The simulated results show that the proposed method can increase the convergence rate by more than 20%, compared with the back-propagation (BP), SA, and restricted Boltzmann machines based extreme learning machine (RBM-ELM) algorithms. The comparative cognition experiments prove that the method can obtain better performances of information understanding and fault-tolerant learning, and the cognition accuracies for original sample, damaged sample, and transformed sample can reach 99.6%, 99.2%, and 97.1%, respectively.

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Section: Sa-ann-based Cognition Mechanismmentioning

confidence: 99%

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

Chen

Tan

2018

Complexity

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“…where is the system gain factor, is the lag time, = / is the time constant, is system specific heat, and is radiating coefficient [3,4,[25][26][27]. Therefore, it will be with apparent variations according to the different control objectives and environmental conditions.…”

Section: Control Objective and Thermodynamic Modelmentioning

confidence: 99%

A Self‐Tuning Proportional‐Integral‐Derivative‐Based Temperature Control Method for Draw‐Texturing‐Yarn Machine

Rong

Chen

2017

Mathematical Problems in Engineering

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Owing to the fast time-varying characteristics, the temperature control for draw-texturing-yarn (DTY) machine has higher technical difficulties and results in challenges for system energy optimization. To address the matter, a self-tuning proportionalintegral-derivative-(ST-PID-) based temperature control method is proposed. Referring to the technical procedures of DTY machine, a thermodynamic model is set up. Then, a ST-PID minimum phase control system is constructed by the pole-point placement method. Subsequently, an artificial neural network based forgetting factor searching (ANN-FFS) algorithm is developed to optimize the system parameter identification. The numerical cases show that the proposed ANN-FFS algorithm can improve the parameter identification process, and the average identifying efficiency ( > 15) can increase by more than 50%; compared with the fuzzy PID controller, the proposed ST-PID method can increase the control accuracy nearly 3 times for the static temperature ascending. The experimental results prove that the proposed ST-PID method has better abilities of characteristics tracing and antiinterference and can restrain the temperature fluctuation caused by objective switching and the factual control accuracy reaches 3 times that of fuzzy PID method.

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“…In this mode each inverter is operated as a two-level inverter and the decoupled space vector PWM is used to generate the gating pulses. By using the decoupled SVPWM technique, harmonics at first center band can also be cancelled which will improve the harmonic profile of the output voltage [12]- [13]. …”

Section: Five-level Inverter Configurationmentioning

confidence: 99%

A five-level inverter topology for four pole induction motor drive using four two-level inverters and two isolated DC sources

Nallamekala

Umesh

Sivakumar

2014

2014 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES)

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In this paper, a five-level inverter configuration is presented to improve the voltage and current harmonic profile. This topology is constructed based on the stator winding configuration of a four pole induction motor. Identical voltage profile winding coils of four pole induction motor are disconnected and fed with four two-level inverters. These four inverters are supplied with two isolated dc sources to block the path for zero sequence currents through the motor phase windings. Level shifted carrier based SVPWM is used to produce the gating signals which will increase the dc bus utilization by 15%. Two two-level inverters are feeding one winding and producing three-level voltage waveform. Similarly remaining two two-level inverters are producing a three-level voltage waveform across the other winding. By providing 180 0 phase shift between carrier waves, multi-level voltage waveform is produced across the total winding and also first center band harmonics are cancelled. The proposed topology is simulated in MATLAB/ Simulink and experimentally verified with 5hp four pole induction motor drive.

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Multiple-Loop Digital Control Method for a 400-Hz Inverter System Based on Phase Feedback

Cited by 53 publications

References 25 publications

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

A SA‐ANN‐Based Modeling Method for Human Cognition Mechanism and the PSACO Cognition Algorithm

A Self‐Tuning Proportional‐Integral‐Derivative‐Based Temperature Control Method for Draw‐Texturing‐Yarn Machine

A five-level inverter topology for four pole induction motor drive using four two-level inverters and two isolated DC sources

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