This paper proposes two methods of maximum power point tracking using a fuzzy logic and a neural network controllers for photovoltaic systems. The two maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and estimated the optimum duty cycle corres...
Besides, this study thoroughly compares the Bilayered Neural Network (BNN) and ANFIS models on various scales. Whilst the ANFIS model is extremely stable for almost all numbers of membership functions, the BNN model is highly sensitive to this scale factor to predict DPT. 展开 ...
Using B-spline neural network to extract fuzzy rules for a centrifugal pump monitoring In mechanical equipment monitoring tasks, fuzzy logic theory has been applied to situations where accurate mathematical models are unavailable or too compl... K Wang,L Bing - 《Journal of Intelligent Manufacturing...
A feedforward neural network received the machine terminal signals at the input and calculated flux, torque and unit vectors at the output, which were then used in the control of a direct vector-controlled drive system. The application of fuzzy logic to the estimation of power electronic ...
RETRACTED: Neural network-based fuzzy logic parallel distributed compensation controller for structural system The objective of this paper is to review some important progress with H infinity control methods and to derive an artificial algorithm for dealing with sta... Chen,C.-W. - 《Journal of Vi...
This paper discusses a congestion avoidance and control scheme based on the application of fuzzy logic theory and its neural network implementation. It is mainly concerned with high-speed wide area networks where propagation delays can have significant effects on closed-loop traffic control. In order...
A recurrent, neural network-based fuzzy logic system includes neurons in a rule base layer which each have a recurrent architecture with an output-to-input feedback path including a time delay element and a neural weight. Further included is a neural network-based, fuzzy logic finite state mach...
7.2 Artificial neural network and fuzzy logic 7.2.1 Artificial neural network The artificial neural network (ANN) is a potent data-modelling tool that is able to capture and represent any kind of input–output relationships. Here one or more hidden layers, which consist of a certain number of...
Perhaps, unsurprisingly, when I started to look into Fuzzy Logic, the problems of rules raised its head again to the point where I came up with the ideas I talk about in theFuzzy Logic Vs Adaline Neural Networkarticle. In that article, I also express my own doubts about whether what I ...
In addition, by introducing a first-order filter and the approximation properties of fuzzy logic systems, the problem of repeated differentiation of the virtual controllers and the issue of the algebraic loop in the backstepping method are avoided. (3) Different from the existing results [32], [...