Modeling flexible plate structure system with free-free-clamped-clamped (FFCC) edges using Particle Swarm Optimization
This paper presents the performance of system identification for rectangular flexible plate using conventional parametric modeling approach by Recursive Least Squares (RLS) and intelligent parametric modeling approach by Particle swarm Optimization (PSO). The experimental rig of rectangular flexible plate with free-free-clamped-clamped edges boundary condition designed and fabricated in this research. The experimental study was conducted to collect the input-output data using a vibration flexible plate complete with data acquisition and instrumentation system. The input-output data will be used during developed the system identification. The whole developed model using RLS and PSO were validated using mean squares error (MSE), one step ahead prediction (OSA) and correlation test. The estimated of developed models was found are comparable, acceptable and possible to be used as a platform of controller development later on. As a comparison between developed system, it was found that the Particle Swarm Optimization algorithm has perform better in term of the lowest mean squares error which is 0.00032719.
Implementation of swarm algorithm in modeling a flexible beam structure
The application of System Identification techniques for modeling a flexible beam structure are presented in this paper. The flexible beam has been widely applied in various fields engineering and industrial. However, the flexible structure is easily influenced by unwanted vibration which may lead to fatigue, performance reduction and structure damage. Thus, the unwanted vibration must be controlled and reduced. In order to have a good controller performance for vibration suppression, an appropriate model of flexible beam is required. Hence, to obtain a model of the flexible beam structure, Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) are implemented in this study as System Identification techniques. The implementation of PSO and ABC requires experimental data input and output retrieved from data acquisition from a well-developed experimental test rig via MATLAB Simulink platform. Results obtained are displayed in graphical plots and numerical values. The predicted model is validated via mean square error (MSE) and correlation tests. To represent the dynamic model of the flexible beam structure, model with minimum MSE value and correlation test within 95 % confidence interval is selected as the best fit model. The result shows that PSO algorithm produces better performance compared to ABC algorithm with a 3rd order predicted model that has lowest MSE value and correlation tests within 95 % confidence interval for the beam system.
Neuronal uptake inhibitors, nisoxetine and fluoxetine on rat vascular contractions.
The importance of neuronal uptake processes in rat arteries and veins was compared using nisoxetine and fluoxetine, selective inhibitors for neuronal uptake of norepinephrine and serotonin, respectively. Nisoxetine (10(-7) - 10(-5) M) increased the sensitivity to exogenous norepinephrine in the portal and mesenteric veins (10-fold) and in the mesenteric artery (2.5-fold). Responses to field stimulation were also increased afternisoxetine in all three vessels. After nisoxetine, aortic responses to norepinephrine were unaltered and in all tissues, serotonin-induced contractions were reduced. Fluoxetine did not potentiate responses to norepinephrine or to field stimulation except in the mesenteric vein where sensitivity to norepinephrine was increased and the relaxation rate after field stimulation was prolonged. Although serotonin has been detected in blood vessels, fluoxetine did not increase vascular responses to serotonin. These studies suggest that rat mesenteric veins have a highly sensitive neuronal uptake mechanism of norepinephrine. Furthermore, these data provide indirect evidence against a functionally important serotonergic uptake process in rat blood vessels and suggest that neuronal uptake of serotonin does not exert a major role in terminating the vascular action of this biogenic amine.