Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement

Background: A multi-motor synchronous drive control system is widely used in many fields, such as electric vehicle drive, paper making, and printing. Methods: On the basis of the optimized structure of ADRC, a fuzzy first-order active disturbance rejection controller was developed. Double channels compensation of extended state observer was employed to estimate and compensate the total disturbances, and an approximate linearization and deterministic system was obtained. As the parameters of ADRC are adjusted online by a fuzzy controller, the performance of the controller is effectively improved. Results: Based on the SIMATIC S7-300 induction motor control experimental platform, the performances of anti-interference and tracking performance are tested. Conclusion: The actual experimental results indicated that compared with PID control, induction motor drive system controlled by fuzzy ADRC has higher dynamic and static status and following performances and stronger anti-interference abilities.

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Single-Phase Induction-Motor Performance Calculation

Transactions of the American Institute of Electrical Engineers ◽

10.1109/t-aiee.1941.5058277 ◽

1941 ◽

Vol 60 (2) ◽

pp. 55-58 ◽

Cited By ~ 4

Author(s):

F. S. Himebrook

Keyword(s):

Induction Motor ◽

Motor Performance ◽

Single Phase ◽

Performance Calculation

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Tailoring induction motor analytical models to fit known motor performance characteristics and satisfy particular study needs

IEEE Transactions on Power Systems ◽

10.1109/59.119235 ◽

1991 ◽

Vol 6 (3) ◽

pp. 959-965 ◽

Cited By ~ 41

Author(s):

B.K. Johnson ◽

J.R. Willis

Keyword(s):

Induction Motor ◽

Motor Performance ◽

Performance Characteristics ◽

Analytical Models

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Assessment of induction motor performance under voltage unbalance condition

2012 IEEE 15th International Conference on Harmonics and Quality of Power ◽

10.1109/ichqp.2012.6381280 ◽

2012 ◽

Cited By ~ 12

Author(s):

Shashi Bhushan Singh ◽

Asheesh K. Singh ◽

Padmanabh Thakur

Keyword(s):

Induction Motor ◽

Motor Performance ◽

Voltage Unbalance

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Neuro Fuzzy Controller for DTC of Induction Motor Using Multilevel Inverter with SVM

Journal of Circuits System and Computers ◽

10.1142/s0218126621502509 ◽

2021 ◽

pp. 2150250

Author(s):

B. Kiran Kumar ◽

Y. V. Siva Reddy ◽

M. Vijaya Kumar

Keyword(s):

Induction Motor ◽

Fuzzy Logic Controller ◽

Fuzzy Controller ◽

Reference Voltage ◽

Training Dataset ◽

Testing Time ◽

Hybrid Technique ◽

Nonlinear Loads ◽

Neuro Fuzzy ◽

Voltage Signal

In this paper, an effective neuro-fuzzy controller (NFC) technique has been proposed to control the induction motor torque and flux. The NFC hybrid technique is the grouping of the neural network (NN) and fuzzy logic controller (FLC), which generated the target voltages with the corresponding input flux and torque. The novelty of the proposed hybrid technique is highly flexible in nonlinear loads, convenient user interface and logical intellectual and permitting for integrated controlling schemes. Here, the FLC generates the training dataset of the NN technique based on the logical rules. The generated dataset contains the information about the flux and torque deviation parameters and the corresponding reference voltage parameters. The NN has been trained based on training dataset and the testing time which produces the optimal reference voltage parameters depends on the variation of the torque and flux parameters. By using the output of the NFC technique, the space vector modulation (SVM) develops the appropriate control pulses to the five-level inverter and the inverter generates the output voltage signal to the induction motor. The proposed method is designed in the MATLAB/Simulink platform and the outputs are verified through the comparison analysis with the existing techniques.

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The role of inhibition in motor performance and learning

Brain Stimulation ◽

10.1016/j.brs.2017.01.238 ◽

2017 ◽

Vol 10 (2) ◽

pp. 417 ◽

Cited By ~ 1

Author(s):

J. Kolasinski ◽

A. Johnstone ◽

V. Bachtiar ◽

C.J. Stagg

Keyword(s):

Motor Performance

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Visual Illusions Affect Motor Performance, But not Learning in Highly Skilled Shooters

Journal of Motor Learning and Development ◽

10.1123/jmld.2017-0011 ◽

2018 ◽

Vol 6 (2) ◽

pp. 220-233 ◽

Cited By ~ 3

Author(s):

Moslem Bahmani ◽

Jed A. Diekfuss ◽

Robabeh Rostami ◽

Nasim Ataee ◽

Farhad Ghadiri

Keyword(s):

Self Efficacy ◽

Retention Test ◽

Motor Performance ◽

Visual Illusions ◽

Limited Information ◽

Ebbinghaus Illusion ◽

Optimal Theory ◽

Highly Skilled ◽

Stages Of Learning

Enhanced expectancies are an important component of OPTIMAL theory and are thought to contribute to motor performance and learning. There is limited information, however, on the generalizability of OPTIMAL theory to highly skilled individuals. The purpose of this study was to examine the effects of visual illusions, specifically an Ebbinghaus illusion, on the performance and learning of an aiming task using highly skilled 10-m rifle and pistol shooters. Two groups of shooters with international experience were recruited and practiced with perceived larger and smaller targets. Our results indicated that participants who perceived the target larger reported higher self-efficacy immediately after practice. In addition, these participants had higher shooting performance during practice. Our retention test (24 hours later), however, did not produce differences in self-efficacy or shooting performance. Our data suggests that visual illusions are beneficial for motor performance in highly skilled shooters, but may not affect learning in those who are in the latter stages of learning. Further studies should continue examining the role of visual illusions for enhancing expectancies in highly skilled and experienced performers.

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Modelling Cationic Diffusion in Nickel-Based Honeycomb Layered Tellurates using Vashishta-Rahman Interatomic Potential and Relevant Insights

10.26434/chemrxiv.13522076.v2 ◽

2021 ◽

Author(s):

Kartik Sau ◽

Tamio Ikeshoji ◽

Godwill Mbiti Kanyolo ◽

Titus Masese

Keyword(s):

Performance Enhancement ◽

Interatomic Potential ◽

Theoretical Studies ◽

Layered Oxides ◽

Ionic Radii ◽

Diffusion Channel ◽

Exponential Increase ◽

Potential Parameters ◽

Insight Into

Although the fascinatingly rich crystal chemistry of honeycomb layered oxides has been accredited as the propelling force behind their remarkable electrochemistry, the atomistic mechanisms surrounding their operations remain unexplored. Thus, herein, we present an extensive molecular dynamics study performed systematically using a refined set of inter-atomic potential parameters of A2Ni2TeO6 (where A = Li, Na, and K). We demonstrate the effectiveness of the Vashishta-Rahman form of the interatomic potential in reproducing various structural and transport properties of this promising class of materials and predict an exponential increase in cationic diffusion with larger interlayer distances. The simulations further demonstrate the correlation between broadened inter-layer (inter-slab) distances associated with the larger ionic radii of K and Na compared to Li and the enhanced cationic conduction exhibited in K2Ni2TeO6 and Na2Ni2TeO6 relative to Li2Ni2TeO6. Whence, our findings connect lower potential energy barriers, favourable cationic paths and wider bottleneck size along the cationic diffusion channel within frameworks (comprised of larger mobile cations) to the improved cationic diffusion experimentally observed in honeycomb layered oxides. Furthermore, we explicitly study the role of inter-layer distance and cationic size in cationic diffusion. Our theoretical studies reveal the dominance of inter-layer distance over cationic size, a crucial insight into the further performance enhancement of honeycomb layered oxides.

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Modelling Cationic Diffusion in Nickel-Based Honeycomb Layered Tellurates using Vashishta-Rahman Interatomic Potential and Relevant Insights

10.26434/chemrxiv.13522076.v4 ◽

2021 ◽

Author(s):

Kartik Sau ◽

Tamio Ikeshoji ◽

Godwill Mbiti Kanyolo ◽

Titus Masese

Keyword(s):

Performance Enhancement ◽

Interatomic Potential ◽

Layered Oxides ◽

Ionic Radii ◽

Diffusion Channel ◽

Atomic Potential ◽

Exponential Increase ◽

Potential Parameters ◽

Insight Into

Although the fascinatingly rich crystal chemistry of honeycomb layered oxides has been accredited as the propelling force behind their remarkable electrochemistry, the atomistic mechanisms surrounding their operations remain unexplored. Thus, herein, we present an extensive molecular dynamics study performed systematically using a reliable set of inter-atomic potential parameters of A2Ni2TeO6 (where A = Li, Na, and K). We demonstrate the effectiveness of the Vashishta-Rahman form of the inter-atomic potential in reproducing various structural and transport properties of this promising class of materials and predict an exponential increase in cationic diffusion with larger inter-layer distances. The simulations demonstrate the correlation between broadened inter-layer (inter-slab) distances associated with the larger ionic radii of K and Na compared to Li and the enhanced cationic conduction exhibited in K2Ni2TeO6 and Na2Ni2TeO6 relative to Li2Ni2TeO6. Whence, our findings connect lower potential energy barriers, favourable cationic paths and wider bottleneck size along the cationic diffusion channel within frameworks (comprised of larger mobile cations) to the improved cationic diffusion experimentally observed in honeycomb layered oxides. Furthermore, we elucidate the role of inter-layer distance and cationic size in cationic diffusion. Our theoretical studies reveal the dominance of inter-layer distance over cationic size, a crucial insight into the further performance enhancement of honeycomb layered oxides.

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