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Abstract: Particle swarm optimization (PSO ) is an effective & reliable evolutionary based approach .
Yuhui Shi and Russell Eberhart "A modified particle swarm optimizer" 0- 7803-4869-9198 0.0001998 IEEE.
In the real world, everything that occurs results from the interaction between atoms (and sub-particles of those atoms). If we were to simulate the world in a computer, we would have to simulate this interaction based on the simple laws of physics. Domenico Prattichizzo,, and Antonio Bicchi,"Dynamic "Analysis of Mobility and Graspability of General Manipulation Systems" IEEE transactions on robotics and automation, vol. This paper presents a review of PSO application in Economic Load Dispatch problems. Stukenbrock, "Toward maximum flexibility in working machinery, iht control in a mecalac excavator," 2004. Yao, "Energy-saving control of singlerod hydraulic cylinders with programmable valves and improved working mode selection," 2002. Eriksson, "Control Strategy for Energy Efficient Fluid Power Actuators: Utilizing Individual Metering," SE-581 83 Linköping, Sweden: Linköping University, 2007. There are various field of power system in which PSO is successfully applied. (April 2003), "Nanometer stepping drives of surface acoustic wave motor", IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 50, IEEE, pp. Due to its higher quality solution including mathematical simplicity, fast convergence & robustness it has become popular for many optimization problems. Conventional hydraulic cylinders are simulated in FLUENT. Singh, "Derivation of design requirements for optimization of a high performance hydrostatic actuation system," International Journal of Fluid Power, vol. Results show that the small outlet ports are the sources of energy loss in hydraulic cylinders.