BACKGROUND Human balance during quiet standing is influenced by adding mass to the body with a backpack, with symmetrically-applied loads to the trunk, or with obesity. Adding mass to the body increases both the weight and inertia of the body, which theoretically could provide counteracting effects on body dynamics and balance. Understanding the independent effects of adding weight and inertia ...

A Maglev system was modeled by the exact feedback linearization to achieve two same linear subsystems. The proportional-integral-differential controllers (PID) based on particle swarm optimization (PSO) algorithm with four different inertia weights were then used to regulate both linear subsystems. These different inertia weights were Fixed Inertia Weight (FIW), Linear Descend Inertia Weight (L...

algorithm was applied to the two-dimensional non-guillotine rectangular packing problems. In this study, two different weight mechanisms in the PSO algorithm are used: fixed inertia weight and nonlinear varying inertia weight. The nonlinear varying inertia weights help to improve the speed of convergence and the search ability. In order to compare the performances of these weight mechanisms, a ...

In Particle Swarm Optimization (PSO), setting the inertia weight w is one of the most important topics. The inertia weight was introduced into PSO to balance between its global and local search abilities. In this paper, first, we propose a method to adaptively adjust the inertia weight based on particle’s velocity information. Second, we utilize both position and velocity information to adaptiv...

This paper presents an alternative and efficient method for solving the optimal control of single-stage hybrid manufacturing systems which are composed with two different categories: continuous dynamics and discrete dynamics. Three different inertia weights, a constant inertia weight (CIW), time-varying inertia weight (TVIW), and global-local best inertia weight (GLbestIW), are considered with ...

This paper proposes an efficient method to solve the optimal power flow problem in power systems using Particle Swarm Optimization PSO . The objective of the proposed method is to find the steady-state operating point which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow, and voltage. Three different inertia weights, a...

Inertia weight is one of the most important adjustable parameters of particle swarm optimization (PSO). The proper selection of inertia weight can prove a right balance between global search and local search. In this paper, a novel PSOs with non-linear inertia weight based on the arc tangent function is provided. The performance of the proposed PSO models are compared with standard PSO with lin...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

Impact of Acceleration Coefficient Strategies with Random Neighborhood Topology in Particle Swarm Optimization Mrs. Snehal Mohan Kamalapur, Dr. Varsha Hemant Patil Research Scholar, Research Guide DYPIET, Vice Principal, MCERC, Pune , Nashik India Abstract: Particle Swarm Optimization is optimization technique having few parameters to tune. Inertia Weight with velocity clamping has great impact...