H.6.2.2. Fuzzy set
1. Improvement of Rule Generation Methods for Fuzzy Controller

N. Mohammadkarimi; V. Derhami

Volume 8, Issue 1 , Winter 2020, , Pages 49-54


  This paper proposes fuzzy modeling using obtained data. Fuzzy system is known as knowledge-based or rule-bases system. The most important part of fuzzy system is rule-base. One of problems of generation of fuzzy rule with training data is inconsistence data. Existence of inconsistence and uncertain states ...  Read More

H.6.2.2. Fuzzy set
2. Identification of Cement Rotary Kiln in Noisy Condition using Takagi-Sugeno Neuro-fuzzy System

N. Moradkhani; M. Teshnehlab

Volume 7, Issue 3 , Summer 2019, , Pages 367-375


  Cement rotary kiln is the main part of cement production process that have always attracted many researchers’ attention. But this complex nonlinear system has not been modeled efficiently which can make an appropriate performance specially in noisy condition. In this paper Takagi-Sugeno neuro-fuzzy ...  Read More

H.6.2.2. Fuzzy set
3. Developing a Course Recommender by Combining Clustering and Fuzzy Association Rules

Sh. Asadi; Seyed M. b. Jafari; Z. Shokrollahi

Volume 7, Issue 2 , Spring 2019, , Pages 249-262


  Each semester, students go through the process of selecting appropriate courses. It is difficult to find information about each course and ultimately make decisions. The objective of this paper is to design a course recommender model which takes student characteristics into account to recommend appropriate ...  Read More

H.6.2.2. Fuzzy set
4. Direct adaptive fuzzy control of flexible-joint robots including actuator dynamics using particle swarm optimization

M. Moradizirkohi; S. Izadpanah

Volume 5, Issue 1 , Winter 2017, , Pages 137-147


  In this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. The design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a PID ...  Read More

A.2. Control Structures and Microprogramming
5. Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

M. M. Fateh; S. Azargoshasb

Volume 3, Issue 1 , Winter 2015, , Pages 113-120


  This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances ...  Read More