Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence
In order to improve the performance of a Proportional-Integral-Derivative (PID) controller used in the control of Linear Induction Motor (LIM) V/f speed, this research presents a bio-inspired meta-heuristic soft computing approach. A PID controller specifically designed for the LIM system is describ...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Franklin Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773186324001130 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846115541052293120 |
|---|---|
| author | Vineet Shekher Aayush Sisodiya Ashutosh Kumar Sinha Himanshu Harsh Nirmala Soren |
| author_facet | Vineet Shekher Aayush Sisodiya Ashutosh Kumar Sinha Himanshu Harsh Nirmala Soren |
| author_sort | Vineet Shekher |
| collection | DOAJ |
| description | In order to improve the performance of a Proportional-Integral-Derivative (PID) controller used in the control of Linear Induction Motor (LIM) V/f speed, this research presents a bio-inspired meta-heuristic soft computing approach. A PID controller specifically designed for the LIM system is described in detail, with a focus on how to optimize the controller using an evolutionary strategy that makes use of the Nutcracker Optimizer. Settling time, rise time, maximum overshoot, and ITAE (Integral-Time Absolute Error) are examples of transient response specifications that are achieved in MATLAB/Simulink by using a step input to the LIM and the optimal set of PID parameters chosen from the optimization. In order to determine the most effective technique for obtaining the optimum response in LIM, these outcomes are then contrasted with outcomes from other soft computing techniques. |
| format | Article |
| id | doaj-art-88f3ab29b7ff46ca94c6d6302f8145e1 |
| institution | Kabale University |
| issn | 2773-1863 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Franklin Open |
| spelling | doaj-art-88f3ab29b7ff46ca94c6d6302f8145e12024-12-19T11:03:33ZengElsevierFranklin Open2773-18632024-12-019100183Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligenceVineet Shekher0Aayush Sisodiya1Ashutosh Kumar Sinha2Himanshu Harsh3Nirmala Soren4Department of Electrical Engineering, Goverment Engineering College, Palamu, Jharkhand, IndiaDepartment of Electrical Engineering, BIT Sindri, Jharkhand, India; Corresponding author.Department of Electrical Engineering, BIT Sindri, Jharkhand, IndiaDepartment of Electrical Engineering, BIT Sindri, Jharkhand, IndiaDepartment of Electrical Engineering, BIT Sindri, Jharkhand, IndiaIn order to improve the performance of a Proportional-Integral-Derivative (PID) controller used in the control of Linear Induction Motor (LIM) V/f speed, this research presents a bio-inspired meta-heuristic soft computing approach. A PID controller specifically designed for the LIM system is described in detail, with a focus on how to optimize the controller using an evolutionary strategy that makes use of the Nutcracker Optimizer. Settling time, rise time, maximum overshoot, and ITAE (Integral-Time Absolute Error) are examples of transient response specifications that are achieved in MATLAB/Simulink by using a step input to the LIM and the optimal set of PID parameters chosen from the optimization. In order to determine the most effective technique for obtaining the optimum response in LIM, these outcomes are then contrasted with outcomes from other soft computing techniques.http://www.sciencedirect.com/science/article/pii/S2773186324001130Speed controlLinear induction motor (LIM)Optimization methodsIntegral-time absolute error (ITAE)Improved-grey wolf optimizer (I-GWO)Nutcracker Optimization Algorithm (NOA) |
| spellingShingle | Vineet Shekher Aayush Sisodiya Ashutosh Kumar Sinha Himanshu Harsh Nirmala Soren Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence Franklin Open Speed control Linear induction motor (LIM) Optimization methods Integral-time absolute error (ITAE) Improved-grey wolf optimizer (I-GWO) Nutcracker Optimization Algorithm (NOA) |
| title | Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence |
| title_full | Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence |
| title_fullStr | Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence |
| title_full_unstemmed | Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence |
| title_short | Optimal tuning of PID controller for V/f control of linear induction motor using artificial biological intelligence |
| title_sort | optimal tuning of pid controller for v f control of linear induction motor using artificial biological intelligence |
| topic | Speed control Linear induction motor (LIM) Optimization methods Integral-time absolute error (ITAE) Improved-grey wolf optimizer (I-GWO) Nutcracker Optimization Algorithm (NOA) |
| url | http://www.sciencedirect.com/science/article/pii/S2773186324001130 |
| work_keys_str_mv | AT vineetshekher optimaltuningofpidcontrollerforvfcontroloflinearinductionmotorusingartificialbiologicalintelligence AT aayushsisodiya optimaltuningofpidcontrollerforvfcontroloflinearinductionmotorusingartificialbiologicalintelligence AT ashutoshkumarsinha optimaltuningofpidcontrollerforvfcontroloflinearinductionmotorusingartificialbiologicalintelligence AT himanshuharsh optimaltuningofpidcontrollerforvfcontroloflinearinductionmotorusingartificialbiologicalintelligence AT nirmalasoren optimaltuningofpidcontrollerforvfcontroloflinearinductionmotorusingartificialbiologicalintelligence |