Relating an arm Cartesian space to joint space and arm dynamics, is an essential issue in arm control that has been given a substantial attention by number of researches. Arm inverse kinematic, is a nonlinear relation, and a closed form solution is not a straight forward, or does not even always exist. This research is presenting a practical use of Neuro-Fuzzy system to solve inverse kinematics...

This paper presents the design and implementation of a systematic fuzzy modelling methodology for the inverse dynamic modelling of robot manipulators. The fuzzy logic modelling methodology is motivated in part by the difficulties encountered in the modelling of complex nonlinear uncertain systems, and by the objective of developing an efficient dynamic model for the real-time model-based contro...

in this paper we study two important concepts, i.e. the direct andthe inverse limit of hyperstructures associated with fuzzy sets of type 2, andshow that the direct and the inverse limit of hyperstructures associated withfuzzy sets of type 2 are also hyperstructures associated with fuzzy sets of type 2.

In this paper, the problem of minimum-time trajectory planning is studied for a three degrees-offreedom (3-DOF) planar manipulator using a hierarchical hybrid neuro-fuzzy system. A first preprocessing step involves two components. The first component is NeFIK (for Neuro-Fuzzy Inverse Kinematics), a neuro-fuzzy network designed to learn and solve the inverse kinematics problem. The second one is...

pulse-width modulated (pwm) adjustable frequency drives (afds) are extensively used in industries for control of induction motors. it has led to significant advantages in terms of the performance, size, and efficiency but the output voltage waveform no longer remains sinusoidal. hence, overshoots, high rate of rise, harmonics and transients are observed in the voltage wave. they increase voltag...

In this paper we present a comparison of two fuzzy-control approaches that were developed for use on a non-linear single-input singleoutput (SISO) system. The first method is Fuzzy Model Reference Learning Control (FMRLC) with a modified adaptation mechanism that tunes the fuzzy inverse model. The basic idea of this method is based on shifting the output membership functions in the fuzzy contro...

In this paper, we present a solution of an arbitrary general fully fuzzy linear systems (FFLS) in the form Ã⊗ x̃ = b̃. Where coefficient matrix à is anm×n fuzzy matrix and all of this system are elements of LR type fuzzy numbers. Our method discuss a general FFLS (square or rectangle fully fuzzy linear systems with trapezoidal or triangular LR fuzzy numbers). To do this, we transform fully fuzzy ...

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...

Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...