Brushless motors are widely used in industrial, domestic and electronic equipment today due to their high reliability, high efficiency, low maintenance and many other advantages. But they also have disadvantages, including electronic commutation, and this requires a spe More
Brushless motors are widely used in industrial, domestic and electronic equipment today due to their high reliability, high efficiency, low maintenance and many other advantages. But they also have disadvantages, including electronic commutation, and this requires a speed controller (speed) for this type of engine. In recent decades, a large number of speed controllers have been designed to control the speed of brushless motors. Typically, a derivative-integral-proportional controller is the optimal choice for controlling the speed of brushless motors. By designing the parameters of the derivative-integral-proportional control system, the speed of the brushless motors can be controlled. There are many ways to obtain the optimal derivative-integral-proportional control parameters. One of the methods that has been widely used to obtain and design derivative-integral-proportional control parameters are optimization algorithms. Water cycle optimization algorithm is an optimization algorithm that is used to optimize derivative-integral-proportional control parameters. In this paper, the derivative coefficient equal to 0, the integral coefficient equal to 0.2259937 and the proportional coefficient equal to 0.00188894 are obtained which gives the stability index equal to 0.01038433, the rise time equal to0.00962 , settling time equal to 0.01492 , peak time equal to 0.01817 , settling min equal to 0.9059. These results are compared with the results obtained from particle swarm algorithms and genetics and show that the water cycle method is better.
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Gearing is one of the most efficient methods of transmitting power from a source to its application with or without change of speed or direction. In this paper, a spur gear model is optimized aiming to maximize its transmission power and minimize its weight. Several des More
Gearing is one of the most efficient methods of transmitting power from a source to its application with or without change of speed or direction. In this paper, a spur gear model is optimized aiming to maximize its transmission power and minimize its weight. Several design variables named as transmitted power, number of pinion teeth, modules, and thickness of gears have been considered during optimization process. For the sake of optimization, two developed metaheuristics named as water cycle and neural net-work algorithms have been examined using MATLAB programming language platform. Besides, obtained optimization results have been validated and analyzed using well-known commercial computer aided engineering software ANSYS. Based on the ob-tained optimization results, optimum design has been found using optimizers and in terms of engineering analysis good agreement has been observed between the applied finite element approach.
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Given the fact that hydropower energy is the third largest source of electricity generation and also the most important renewable energy producer, the optimal use of the huge and expensive source of water is essential. In this study, water cycle metaheuristic algorithm More
Given the fact that hydropower energy is the third largest source of electricity generation and also the most important renewable energy producer, the optimal use of the huge and expensive source of water is essential. In this study, water cycle metaheuristic algorithm was used for optimization of the hydropower operation of Jiroft reservoir located in Halilrood basin (south of Iran) for a period of 223 months (from October 2000 to April 2019). After verifying the reliability of the WCA algorithm using several standard benchmark functions, a model was developed for optimal hydropower operation. The results of the algorithm were compared with the results of known metaheuristic algorithm and Imperialist Competitive Algorithm (ICA). The WCA and ICA algorithms were capable to generate energy 7203.29, and 7138.66 MW during the statistical period, respectively. Also, the objective function value for WCA and ICA, was obtained 4.78, 5.82, respectively. The results were indicated high performance of the WCA in optimization of the hydropower operation.
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