Various methods have been exploited in the blind source separation problems, especially in cocktail party problems. The most commonly used method is the independent component analysis (ICA). Many linear and nonlinear ICA methods, such as the radial basis functions (RBF) and self-organizing map (SOM) methods utilise neural networks and genetic algorithms as optimisation methods. For the contrast function, most of the traditional methods, especially the neural networks, use the gradient descent as an objective function for the ICA method. Most of these methods trap in local minima and consume numerous computation requirements. Three metaheuristic optimisation methods, namely particle, quantum particle, and glowworm swarm optimisation methods are introduced in this study to enhance the existing ICA methods. The proposed methods exhibit better results in separation than those in the traditional methods according to the following separation quality measurements: signal-to-noise ratio, signal-to-interference ratio, log-likelihood ratio, perceptual evaluation speech quality and computation time. These methods effectively achieved an independent identical distribution condition when the sampling frequency of the signals is 8 kHz.
In this paper, the power system stabilizer (PSS) and Thyristor controlled phase shifter(TCPS) interaction is investigated . The objective of this work is to study and design a controller capable of doing the task of damping in less economical control effort, and to globally link all controllers of national network in an optimal manner , toward smarter grids . This can be well done if a specific coordination between PSS and FACTS devices , is accomplished . Firstly, A genetic algorithm-based controller is used. Genetic Algorithm (GA) is utilized to search for optimum controller parameter settings that optimize a given eigenvalue based objective function. Secondly, an optimal pole shifting, based on modern control theory for multi-input multi-output systems, is used. It requires solving first order or second order linear matrix Lyapunov equation for shifting dominant poles to much better location that guaranteed less overshoot and less settling time of system transient response following a disturbance.