1Associate Professor, Department of Mathematics, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: ramesh251989@gmail.com
2Associate Professor, Department of Mathematics, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: delbinprema6@gmail.com
3Assistant Professor, Department of Mathematics, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: buvanasankari@gmail.com
4Assistant Professor, Department of Mathematics, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: nietsushamamaths@nehrucolleges.com
5Assistant Professor, Department of Mathematics, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: spjpmath@gmail.com
6Assistant Professor, Department of Chemistry, Nehru Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India
Email: edisonsrkv2008@gmail.com
The nonlinear dynamical systems play critical roles in the modeling of the complex processes in the spheres of engineering, physics, biology, economics and environmental sciences. Unlike linear systems, nonlinear systems are chaotic in nature, bifurcated, sensitive to initial condition, and hence much more difficult to study and manage. When real world systems are increasingly becoming more complex, observationally rigorous ways to conduct analysis are typically not appropriate in issues of operationalizing performance and stability maximization. Next, the efficient optimization techniques have gained the forefront as the viable devices in optimizing the efficacy, steadiness and stretchability of nonlinear dynamical systems. The paper shows some of the latest optimization techniques that are used to analyse and control nonlinear dynamics including gradient-based optimization techniques, evolutionary techniques, swarm intelligent techniques and artificial intelligence-based techniques. The study makes an attempt at exploring the possibility to make these methods applicable to enhancing the stability of the system, the estimation of the parameters and the control measures in unsophisticated dynamic environments. A comprehensive framework is also promoted which integrates optimization techniques and nonlinear modeling of systems in order to boost the performance of the system in new application areas. Real-life applications in various disciplines such as robotics, energy systems, climatic modeling, financial forecasting as well as biologic systems analysis are also discussed in the paper. The application of experimental tests and by comparison, it is determined that the hybrid optimization methods are highly effective in increasing the speed of the convergence, precision and stability of the solution in the system as compared to the traditional methods. These findings show the greater importance of smart optimization strategies to the solution of real-life problems of nonlinear systems and the practical aids to the interdisciplinary fields of the modern science and engineering.
Keywords: Nonlinear Dynamical Systems, Optimization Algorithms, Evolutionary Computation, Swarm Intelligence, Artificial Intelligence Optimization, Chaos Theory, Control Systems, Real-World Applications.
How to cite this article: Ramesh K, Delbin Prema S, Buvanasankari M, Sushama C, Jothiprakash SP, Edison D. Advanced Optimization Techniques in Nonlinear Dynamical Systems Theory and Real-World Applications. Int J Drug Deliv Technol. 2026;16(8s): 296-304; DOI: 10.25258/ijddt.16.8s.41
Source of support: Nil.
Conflict of interest: None