Particle swarm optimization (PSO) is an algorithm that simple and reliable to complete optimization. The balance between exploration exploitation of PSO searching characteristics maintained by inertia weight. Since this parameter has been introduced, there have several different strategies determine the weight during a train run. This paper describes method adjusting weights using fuzzy signatu...

We analysed the execution of multijoint pointing movements in humans while weight or spring loads were applied to the pointing hand. Visual feedback on arm and hand position was excluded. Movement paths, final positions, and normalized velocity profiles were found to be load-independent, except for the very first movement after a load change. With increasing size of a weight load movement veloc...

Here, we present a detailed analysis of the take-off mechanics in droneflies performing voluntary take-offs. Wing and body kinematics of the insects during take-off were measured using high-speed video techniques. Based on the measured data, the inertia force acting on the insect was computed and the aerodynamic force of the wings was calculated by the method of computational fluid dynamics. Su...

Based on a new adaptive Particle Swarm Optimization algorithm with dynamically changing inertia weight (DAPSO), it is used to optimize parameters in PID controller. Compared to conventional PID methods, the simulation shows that this new method makes the optimization perfectly and convergence quickly.