TY - GEN
T1 - Development of sine cosine toolbox for LabVIEW
AU - Maurya, Shubham
AU - Jain, Mohit
AU - Pachauri, Nikhil
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2020.
PY - 2020
Y1 - 2020
N2 - LabVIEW is one of the prominent programming platforms due to its simplicity and robustness towards hardware design. It finds application in different fields of engineering such as industrial automation, signal processing, instrumentation, control system design and so forth. LabVIEW has a rich ecosystem of toolboxes and libraries for simplifying the improvement in numerous zones of engineering, however, it lacks in optimization toolbox for advanced meta-heuristic algorithms. This is a serious deficiency as there is an astonishing improvement in the field of meta-heuristic algorithm in recent years. Thus, in this article, a potentially acclaimed meta-heuristic named as sine cosine algorithm (SCA) is designed in LabVIEW environment. The designed algorithm is benchmarked on a testbed of six non-trivial functions and compared to existing differential evolution (DE) optimizer in LabVIEW. Statistical analysis of results depicts superior accuracy and stability of SCA in comparison to DE. Further, SCA based PID optimizer is also implemented to show the applicability of the designed algorithm in solving real-world optimization problems.
AB - LabVIEW is one of the prominent programming platforms due to its simplicity and robustness towards hardware design. It finds application in different fields of engineering such as industrial automation, signal processing, instrumentation, control system design and so forth. LabVIEW has a rich ecosystem of toolboxes and libraries for simplifying the improvement in numerous zones of engineering, however, it lacks in optimization toolbox for advanced meta-heuristic algorithms. This is a serious deficiency as there is an astonishing improvement in the field of meta-heuristic algorithm in recent years. Thus, in this article, a potentially acclaimed meta-heuristic named as sine cosine algorithm (SCA) is designed in LabVIEW environment. The designed algorithm is benchmarked on a testbed of six non-trivial functions and compared to existing differential evolution (DE) optimizer in LabVIEW. Statistical analysis of results depicts superior accuracy and stability of SCA in comparison to DE. Further, SCA based PID optimizer is also implemented to show the applicability of the designed algorithm in solving real-world optimization problems.
UR - https://www.scopus.com/pages/publications/85072844422
UR - https://www.scopus.com/pages/publications/85072844422#tab=citedBy
U2 - 10.1007/978-981-13-8618-3_76
DO - 10.1007/978-981-13-8618-3_76
M3 - Conference contribution
AN - SCOPUS:85072844422
SN - 9789811386176
T3 - Advances in Intelligent Systems and Computing
SP - 747
EP - 753
BT - Intelligent Communication, Control and Devices - Proceedings of ICICCD 2018
A2 - Choudhury, Sushabhan
A2 - Mishra, Ranjan
A2 - Mishra, Raj Gaurav
A2 - Kumar, Adesh
PB - Springer Verlag
T2 - 3rd International Conference on Intelligent Communication, Control and Devices, ICICCD 2018
Y2 - 21 December 2018 through 22 December 2018
ER -