The paper discusses about the Choquet Fuzzy Integral (CFI) based identification and control of a Real Time Dynamical System. The plant is modeled using Choquet fuzzy Integral based Neural Network with Gradient Descent as learning algorithm. This model is used for designing and simulating CFI based controller. Then this designed controller is implemented on real time system through MATLAB. Final...

In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...

In this contribution a new supervised classification model is proposed, namely the Fuzzy Evolutionary Probabilistic Neural Network (FEPNN). The proposed model incorporates a fuzzy class membership function into the recently proposed Evolutionary Probabilistic Neural Network (EPNN). EPNN employs an evolutionary algorithm, namely the Particle Swarm Optimization (PSO), for the selection of the spr...

We show that a reinforcement learning method, adaptive critic based approximate dynamic programming, can be used to create fuzzy policy managers for adaptive control of a logistic system. Two different architectures are used for the policy manager, a feed forward neural network, and a fuzzy rule base. For both architectures, policy managers are trained that outperform LP and GA derived fixed po...

Reengineering consists of conceiving the radical improvements that must be introduced into the organization of a manufacturing system so that the product managerial attributes satisfy a target market. Fuzzy cognitive maps are fuzzy signed digraphs that cannot justify their outputs because they are full of feedback loops. This paper presents an intelligent system that supports reengineering. The...

In the paper, a new method of tool wear detection with cutting conditions and detected signals is presented, which includes the model of wavelet fuzzy neural network with acoustic emission (AE) and the model of fuzzy classification with motor current. The results of tool wear estimated by cutting conditions and detected signals (spindle motor current, feed motor current and AE) are fused by fuz...

In this study, the average surface roughness values obtained when turning AISI 4140 grade tempered steel with a hardness of 51 HRC, were modeled using fuzzy logic, artificial neural networks (ANN) and multi-regression equations. Input variables consisted of cutting speed (V), feed rate (f) and depth of cut (a) while output variable was surface roughness (Ra). Fuzzy logic and ANN models were dev...

Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surfa...

In this paper, wavelet transforms and fuzzy techniques are used to monitor tool breakage and wear conditions in real time according to the measured spindle and feed motor currents, respectively. First, the continuous and discrete wavelet transforms are used to decompose the spindle and feed ac servo motor current signals to extract signal features so as to detect the breakage of drills successf...