This paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. In this method, mammograms are segmented into regions of interest (ROI) in order to extract features including geometrical and contourlet coefficients. The extracted features benefit from...

We propose in this paper an enhanced fuzzy P+ID controller to improve control performance in both dynamic transient and steady-state periods for mechanical manipulators under uncertainty. The fuzzy P+ID controller adds only two additional parameters to be tuned relative to the original PID controller. One of these parameters is mainly used to reduce a steady-state error. The other is used to sp...

The Fuzzy State Space algorithm (FSSA) is the main feature in the development of the Fuzzy State Space Model (FSSM) for solving inverse problems in multivariable dynamic systems. Traditionally, such inverse problems have been addressed by repeated simulation of forward problems, which requires excessive computer time and thus can be very costly. In the formulation of the FSSA, the uncertain val...

A programmable logic controller (PC) carries out a control algorithm under violations of the ontological assumptions (VOA) when the plant does not meet one or more unstated but essential assumptions used in the design of the control algorithm. This paper presents a recovery technique based on the theory of Fuzzy State Fuzzy Output Finite State Machines (FSFO-FSM). The appeal of this approach is...

This paper proposes to control the speed of the permanent magnet (PM) DC motor drive using fuzzy logic control (FLC) based on Matlab simulation environment. The proposed speed controller is developed based on fuzzy logic, to minimize maximum overshoot and steady state error. A comparison study and analysis of proposed fuzzy logic control to classical PID control system applied to PM DC motor is...

anti-lock braking system (abs) which is a nonlinear and time variant system may not be easily controlled by classic control methods. this is due to the fact that classic linear controllers are just capable of controlling a specific plant in small region of state space. to overcome this problem, a more powerful control technique must be employed for complex nonlinear plants. fuzzy controllers ar...

This document deals with the problem of passive fuzzy controller design state-derivative feedback approach for nonlinear stochastic singular systems. Recently, systems have a greater focus on literature because they can keep more physical system characteristics than conventional At first, Takagi-Sugeno models are used to represent Then, and parallel distributed compensation method employed cont...

In this paper, we propose a reinforcement learning method called a fuzzy Q-learning where an agent determines its action based on the inference result by a fuzzy rule-based system. We apply the proposed method to a soccer agent that intercepts a passed ball by another agent. In the proposed method, the state space is represented by internal information the learning agent maintains such as the r...

Abstract This paper investigates the problem of H2/H∞ control for discrete fuzzy time delay systems based on Takaqi-Sugeno(T-S) model. The purpose is to design state feedback fuzzy controllers such that the resulting closed-loop system is not only uniformly stable but also satisfied with H2/H∞ performance index. Sufficient conditions for the solvability of the problem are obtained by utilizing ...

In this paper, we study impulsive fuzzy cellular neural networks. Criteria are obtained for the existence and exponential stability of a unique equilibrium of fuzzy cellular neural networks impulsive state displacements at fixed instants of time.