Performance Evaluation of Neurobiologically Inspired Brain Emotional Adaptive Mechanism for Permanent Magnet Synchronous Motor Drive

Qutubuddin,; Yadaiah, N.

doi:10.1007/s13369-021-06111-7

Cited by 4 publications

(3 citation statements)

References 30 publications

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“…In this section, the control system is considered as a general scheme, and the signals are presented parametrically in the form of mathematical equations so that the process integrity can be extended to any other system, and in particular, the equations can be used directly to develop the proposed control model in the later section. Figure 4 illustrates an image of the human brain, and Figure 5 shows the modified sensory signals and a communication model related to the learning network inside the brain [14]. As shown in Figure 5, the amygdala output is a combination of the inhibitory and excitatory signal data.…”

Section: Intelligent Controller Based On Brain Emotional Learningmentioning

confidence: 99%

“…This method is based on the direct connection between input and output through the use of differential geometry theorems and the elimination of nonlinear properties and, as has been specified, it has its own specific complexities. Even intelligent control methods, including fuzzy control, have been well implemented [14], but the important point to be considered along with the responsiveness of these advanced methods is their complexity, which can also increase the cost of hardware.…”

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Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

et al. 2021

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In this paper, intelligent control of a reluctance synchronous motor by an emotional controller, considering the effect of magnetic saturation on implementation, is analyzed; the maximum torque per ampere (MTPA) strategy is provided. According to the application of the proposed control scheme, the structure adequately performs the control of speed and magnetic flux of the reluctance synchronous motor drive. Additionally, the application of intelligent control based on an emotional learning system has provided adequate results to create a proper control process. The control function of a SynRM drive based on vector control in a rotor machine was compared with another based on emotional controllers and a PI controller regulated by genetic algorithms. The result of this comparison was the improvement of control functions by the controller based on the emotional controller. In addition, the MTPA based on search algorithms was well implemented in different situations. Due to its simplicity and independence from system parameters, the emotional controller can be considered as a potential operational method in the industry.

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Section: Intelligent Controller Based On Brain Emotional Learningmentioning

confidence: 99%

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confidence: 99%

Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

et al. 2021

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“…In order to reach a high efficiency compared with the existing BEC, the modified BEC (MBEC) is configured to control the IM drive. Further, to get speed as a feedback signal, The MRAS approach is used in sensorless IM drive to predict rotor position and speed [21].…”

Section: Introductionmentioning

confidence: 99%

Modified Brain Emotional Controller-Based Ripple Minimization for SVM-DTC of Sensorless Induction Motor Drive

Savarapu

Qutubuddin²,

Yadaiah

2022

IEEE Access

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This paper presents the Modified Brain Emotional Controller (MBEC) technique for the minimization of torque and flux ripples of sensorless Induction Motor (IM) drive. In low-speed operation, IM is very sensitive due to variations in torque and flux ripples. These variations inert low order harmonics in stator currents that adversely affect the performance of the IM drive. The drive's performance can be improved by integrating a controller that not only minimizes harmonic presence but also increases the drive's performance. In this paper a biological inspired intelligent speed controller namely, MBEC is proposed to obtain improved performance from the drive. The input to the MBEC is an error of the reference speed and the actual speed of the motor that is estimated using the Model Reference Adaptive System (MRAS). SVM based topology is used to develop the inverter and IM is operated in sensorless DTC technique. Stability analysis of MBEC based IM drive is presented in this paper to hold the effectiveness. The proposed control configuration is tested with different operating conditions and obtained results are verified through real-time experimentation using Opal-RT OP5600. The performance of the proposed control algorithm is compared with the BEC and PI techniques to hold the effectiveness in terms of low flux ripples and torque ripples in different operating conditions.

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Control of heat exchanger using BELBIC

Ramesh,

Yadaiah

2023

LOW RADIOACTIVITY TECHNIQUES 2022 (LRT 2022): Proceedings of the 8th International Workshop on Low Radioactivity Techniques

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Performance Evaluation of Neurobiologically Inspired Brain Emotional Adaptive Mechanism for Permanent Magnet Synchronous Motor Drive

Cited by 4 publications

References 30 publications

Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller

Modified Brain Emotional Controller-Based Ripple Minimization for SVM-DTC of Sensorless Induction Motor Drive

Control of heat exchanger using BELBIC

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