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Abstract

The static synchronous compensator (STATCOM) is the multipurpose FACTS device with the multiple input and multiple output system for the enhancement of its dynamic performance in power system. Based on artificial intelligence (AI) optimization technique, a novel controller is proposed for CSC based STATCOM. In this paper, the CSC based STATCOM is controlled by the LQR. But the best constant values for LQR controller's parameters are obtained laboriously through trial and error method, although time consuming. So the goal of this paper is to investigate the ability of AI techniques such as genetic algorithm (GA) and particle swarm optimization (PSO) methods to search the best values of LQR controller's parameters in a very short time with the desired criterion for the test system. Performances of the GA, PSO & ABC based LQR controllers are also compared. Applicability of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results are shown an improvement in the input-output response of CSC-STATCOM.
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Abstract

The performance of majority engineering systems made of composite laminates can be improved by increasing strength to weight ratio. Variable thickness approach (VTA), in discrete form, used in this study is capable of finding minimum laminate thickness in one stage only, instead of two stage methodology defined by other researchers, with substantial accuracy for the given load conditions. This minimum required laminate thickness can be used by designers in multiple ways. Current study reveals that effectiveness of VTA in this regard depends on ply thickness increment value and number of plies. Maximum Stress theory, Tsai Wu theory and Tsai Hill theory are used as constraints, while ply angles, ply thicknesses and number of plies in discrete form are used as design variables in current simulation studies. Optimization is carried out using direct value coded genetic algorithm. The effect of design variables such as ply angles, ply thicknesses and number of plies in discrete form on optimum solution is investigated considering Uniform Thickness Approach (UTA) and Variable Thickness Approach (VTA) for various load cases.
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