جستجوی مقالات مرتبط با کلیدواژه « الگوریتم زنبور » در نشریات گروه « برق »

Automatic modulation recognition of digital signals is an essential for intelligent communication systems. Most automatic classifications of digital signal types deal with recognizing signals formats in presence of additive white Gaussian noise (AWGN) in channels. However, real world communication environments, such as wireless communication channels, suffer from fading effects. There are few methods proposed to perform in fading channels. This paper presents a high efficient method for identification of M-array phase shift keying (MPSK) digital signal type. The proposed method is heuristic hybrid, formed by a multilayer perceptron (MLP) neural network as the classifier and the bees algorithm (BA) as the optimizer. An equalizer is also used to reduce channel effects. A suitable combination of higher order statistics, up to eighth, is considered as prominent characteristics of signals. Simulation results validate the high efficiency of the proposed technique in recognizing the types of digital signals even at low SNRs.

In this paper, an intelligent integral terminal sliding mode control method with a new sliding surface is proposed based on adaptive neural-fuzzy inference. First, a terminal sliding mode controller using a novel sliding surface is designed based on Lyapunov’s stability theorem for controlling a class of chaotic systems in presence of uncertainty and disturbance. The proposed sliding surface is a combination of the conventional terminal sliding surface and integral of a nonlinear function of the states of the system. The purpose of choosing this surface includes achieving appropriate response speed, removing chattering and robustness against external disturbance. Then, we assume that a nonlinear part of the system is unknown and only input-output data is available. Therefore, an adaptive neuro-fuzzy inference system is used to approximate the unknown part of the system dynamics. Finally, in order to enhance the performance of the proposed method, the honey bee algorithm is utilizd for selecting the coefficients of integral terminal sliding mode controller. The simulation results show the effectiveness of the controller due to the improved speed, removed chattering, appropriate transient response and satisfactory performance in the presence of uncertainties in the system model.

Abstract: Brushless permanent magnet motors play an important role in many applications. Power density and efficiency are two important factors in designing such motors. This paper proposes a novel approach to design a brushless permanent magnet motor based on optimization of a combination of power density and efficiency. First of all, this paper presents the equation related to the design and dimensions of brushless permanent magnet motor. Then, an optimum design based on bees algorithm (BA) with the purpose of increasing power density is presented. Finally, Simulation results of a 2-D finite element analysis have well validated the efficiency of the applied method.