Bio-inspired Optimization Techniques Research Articles

Differential evolution algorithm for simultaneous tuning of excitation and FACTS-based controller

This paper investigates the application of recently developed bio-inspired optimisation technique known as differential evolution (DE) optimisation technique for the simultaneous tuning of excitation and a flexible AC transmission systems (FACTS)-based controller. The design objective is to improve the stability of a power system subjected to a disturbance. The design problem is transformed as an optimisation problem and DE optimisation technique is employed to simultaneously tune the excitation and FACTS-based controller parameters. Non-linear simulation results are presented at various loading conditions and disturbances to show the effectiveness and robustness of the proposed approach. It is observed that the proposed controllers improve greatly the system damping and are robust to variation in operating conditions and type of disturbance.

Optimal design of plasmonic nanostructures for plasmon-interference assisted lithography

We investigate the problem of synthesizing plasmonic nanostructures through the application of a bio-inspired stochastic optimization technique. We show, through some numerical experiments, that the approach proposed could serve as a starting point for the optimal fabrication and characterization of nanometric structures with defined scattering properties. Furthermore, we discuss its possibilities and potential applications.