A Non Linear System Controlling using Constrained based Genetic Algorithm
This article presents the controlling of non-linear system with artificial intelligence (AI) technique. The non- linear system is represented by second order function and genetic algorithm will be used as AI technique. The genetic algorithm involves the three steps: reproduction, crossover, and mutation. The non-linear system is diverging in nature which is showing the non-bounded system and unstable. If the constraints are included in the mathematical expression of the second order system, the performance parameters can be improved. The second order nonlinear system including the constraints is trained by using genetic algorithm (GA). After the implementation of GA, non linear system is converging fast to bounded value or finite region.
Authors
- Niharika Varshney (ORCID: https://orcid.org/0000-0002-8803-8972)
- Deepali Mishra
- Amit Mittal (ORCID: https://orcid.org/0000-0002-1191-4620)
- Vrij Mohan Vidyarthi
- Shivali Pundhir
- Krishnan Bandyopadhyay
Institutions
- Invertis University (IN)
- Graphic Era University (IN)
- Dr. Hari Singh Gour University (IN)
Publication Details
- Published
- 2024-09-18
- DOI
- https://doi.org/10.1109/icosec61587.2024.10722320
- Primary Topic
- Advanced Control Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00