In this paper, we propose a new optimized PID controller to stabilize the synchronous machine connected to an infinite bus. The model for the synchronous machine is 4-ordered linear Philips-Heffron synchronous machine. In this research, the parameters of the PID controller are optimally achieved by minimizing a definite fitness function to removes the unstable Eigen-value to the left side of im...

Particle swarm optimization is one of the evolutionary computations which is inspired by social behavior of bird flocking or fish schooling. This research focuses on the application of the particle swarm optimization to two-dimensional packing problem. Packing problem is a class of optimization problems which involve attempting to pack the items together inside a container, as densely as possib...

In this paper, we propose a new optimized PID controller to stabilize the synchronous machine connected to an infinite bus. The model for the synchronous machine is 4-ordered linear Philips-Heffron synchronous machine. In this research, the parameters of the PID controller are optimally achieved by minimizing a definite fitness function to removes the unstable Eigen-value to the left side of im...

The particle swarm approach provides a low complexity solution to the optimization problem among various existing heuristic algorithms. Recent advances in the algorithm resulted in improved performance at the cost of increased computational complexity, which is undesirable. Literature shows that the particle swarm optimization algorithm based on comprehensive learning provides the best complexi...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithms, which has been applied widely for continuous optimization problems. In this paper, we propose an improved quantum-behaved particle swarm optimization with memory according to the means of best position of particles and using sigal step seaching strategy for sovle the multidimentional prob...

An enhanced particle swarm optimization (EPSO) algorithm is proposed. To improve convergence accuracy and velocity, we introduce a quadratic interpolation method and perturbation to personal best particles in EPSO. Then, a design procedure based on the EPSO is proposed for the design and optimization of equal split broadband microstrip Wilkinson power dividers (MWPDs). A set of numerical exampl...

this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

Antenna arrays are used in many different systems, including radar, military and wireless communications. The design of the antenna array has a significant impact on how well communication system performs. large number pieces sidelobe levels provide biggest hurdles for such arrays. have recently been heavily thinned using optimization approaches that take advantage evolutionary algorithms order...