To provide cost-effective communication systems for separate a signal into different frequency region and eliminate adverse signals and harmonics, Fuzzy Adaptive Modified particle swarm optimization (FAMPSO) method was used to have an optimized gain ripple of 6 order elliptic low pass filter with 300 MHz cut-off frequency. The feasibility and effectiveness of the FAMPSO algorithm is demonstrate...

In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which has been applied to two image analysis tasks. In the former, accurate region-based segmentation is obtained by analyzing the cumulative results of several runs of the algorithm. In the latter, the fast-convergence properties of the algorithm are used to accurately locate and track an object of inte...

In this study, a modified quantum-behaved particle swarm optimization (MQPSO) approach is proposed to design an optimal fuzzy PID controller for asymptotical stabilization of a pendubot system. In the fuzzy PID controller, parameters are determined by using MQPSO algorithm. The MQPSO method and other PSO methods are then applied to design an optimal fuzzy PID controller in a pendubot system. Co...

A modified particle swarm optimization (PSO) approach is presented for the multi-mode resource-constrained scheduling problem of automated guided vehicle (AGV) tasks. Various constraints in process AGV system are analysed, and types quantities AGVs as allocable resources considered. The multiple-AGV combined distribution mode its impact on tasks also Finally, a task model established which obje...

Extending the particle swarm optimization (PSO) algorithm to be one of systemic modeling and controlling tools, several research groups investigate target search with swarm robots (simulated or physical) respectively (Doctor et al., 2004; Hereford & Siebold, 2008; Jatmiko et al., 2007; Marques et al., 2006; Pugh & Martinoli, 2007; Xue & Zeng, 2008). The common idea they hold is to map such swar...

Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in literature. Although original PSO has shown good performance, it still severely suffers from premature convergence. As a result, many researchers have been modifying resulting large number variants with either slightly or significantly better performance. Mainly, standard modified by four main strategie...

Today’s changing electric power systems create a growing need for flexibility, reliability, fast response and accuracy in the fields of electric power generation, transmission, distribution and consumption. Power system networks are complex systems that are nonlinear, disturbances and faults. It can be accomplished by improving the voltage profile, enhancement of voltage stability and by reduci...

This paper investigates into hybridization between PSO and self-adaptive evolutionary programming techniques for solving economic dispatch (ED) problem with non-smooth cost curves where conventional gradient based methods are in-applicable. The convergence capability of evolutionary programming technique is enhanced with hybridization of self-adaptive evolutionary programming technique with PSO...

this paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (pso) algorithm. pso algorithm has been employed 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 logic is proposed to increase the convergenc...