In this paper, aim at the disadvantages of standard Particle Swarm Optimization (PSO) algorithm like being trapped easily into a local optimum, we improves the standard PSO and proposes a new algorithm to solve the overcomes of the standard PSO. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well....

The authors applied the particle swarm optimization (PSO) algorithm to solve the conditional nonlinear optimal perturbation (CNOP) and the lower bound of maximum predictable time (LBMPT). The results obtained by the PSO algorithm were compared to those by the traditional optimization algorithm (such as, a gradient descent algorithm based on the adjoint model, ADJ). The authors found that the PS...

The authors applied the particle swarm optimization (PSO) algorithm to solve the conditional nonlinear optimal perturbation (CNOP) and the lower bound of maximum predictable time (LBMPT). The results obtained by the PSO algorithm were compared to those by the traditional optimization algorithm (such as, a gradient descent algorithm based on the adjoint model, ADJ). The authors found that the PS...

This paper presents a designing an optimal adaptive controller for tracking down the control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been used to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using a logic is proposed to increase the c...

This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. The proposed new algorithm moves particles towards nearby particles of higher fitness, instead of attracting each particle towards just the best position discovered so far by any particle. This is accomplished by usin...

In this paper an extensive theoretical and empirical analysis of recently introduced Particle Swarm Optimization algorithm with Convergence Related parameters (CR-PSO) is presented. The convergence of the classical PSO algorithm is addressed in detail. The conditions that should be imposed on parameters of the algorithm in order for it to converge in mean-square have been derived. The practical...

In this paper, parameter extraction for PSP MOSFET model is demonstrated using Particle Swarm Optimization (PSO) algorithm. I-V measurements are taken on 65 nm technology NMOS devices. For the purpose of comparison, parameter extraction is also carried out using Genetic Algorithm (GA). It is shown that PSO algorithm gives better agreement between measurements and model in comparison to GA and w...

In the paper a modified particle swarm optimization (MPSO) is proposed where concepts from firefly algorithm (FA) are borrowed to enhance the performance of particle swarm optimization (PSO). The modifications focus on the velocity vectors of the PSO, which fully use beneficial information of the position of particles and increase randomization item in the PSO. Finally, the performance of the p...

A new filtering algorithm — PSO-UPF was proposed for nonlinear dynamic systems. Basing on the concept of re-sampling, particles with bigger weights should be re-sampled more time, and in the PSO-UPF, after calculating the weight of particles, some particles will join in the refining process, which means that these particles will move to the region with higher weights. This process can be regard...