This paper presents a new systematic adaptive fuzzy neural network for inverse modelling of robot manipulators. An inductive learning algorithm is applied to generate the required inverse modelling rules from the robot’s input/output records. A full differentiable fuzzy neural network is developed to construct the inverse models of the robot manipulator, while any adaptation technique, such as ...

We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditi...

This paper presents a three-phase grid-connected inverter designed for a 100kW photovoltaic power plant that features a maximum power point tracking (MPPT) scheme based on fuzzy logic. The whole system presented is simulated in Matlab. This fuzzy MPPT shows accurate and fast response, and is integrated in the inverter, so that a DC-DC converter is not needed. The inverter allows full control of...

The measurement of aerodynamic forces and moments acting on an aircraft model is important for the development of wind tunnel measurement technology to predict the performance of the full scale vehicle. The potentials of an aircraft model with and without winglet and aerodynamic characteristics with NACA wing No. 65-3218 have been studied using subsonic wind tunnel of 1 m × 1 m rectangular test...

Ranking competing alternatives in terms of their overall performance with respect to some criterions in fuzzy environment is possible by the use of fuzzy TOPSIS methodology using interval-valued fuzzy-sets concepts. This author presents an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for prioritizing alter...

Abstract: Classical cost efficiency (CE) measurement models require exact and accurate knowledge of the input and output values for each decision making unit (DMU). However, the observed values of the input and output data in real-world problems are often imprecise or vague. In recent years, fuzzy data envelopment analysis (DEA) has been successfully used to deal with imprecise or vague data in...

Ranking competing alternatives in terms of their overall performance with respect to some criterions in fuzzy environment is possible by the use of fuzzy TOPSIS methodology using interval-valued fuzzy-sets concepts. This author presents an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for prioritizing alter...

The optimistic multigranulation T-fuzzy rough set model was established based on multiple granulations under T-fuzzy approximation space by Xu et al., 2012. From the reference, a natural idea is to consider pessimistic multigranulation model in T-fuzzy approximation space. So, in this paper, the main objective is to make further studies according to Xu et al., 2012. The optimistic multigranulat...

This paper proposes a fuzzy-identification-based adaptive control scheme for the chaotic dynamic systems using backstepping control approach, which is referenced as adaptive fuzzy backstepping control (AFBC). The proposed AFBC offers a design approach to drive the chaotic trajectory to track a desired trajectory, and it is comprised of a fuzzy backstepping controller and a robust controller. Th...

Suspension system of a vehicle is used to minimize the effect of different road disturbances for ride comfort and improvement of vehicle control. A passive suspension system responds only to the deflection of the strut. The main objective of this work is to design an efficient active suspension control for a full car model with 8-Degrees Of Freedom (DOF) using adaptive soft-computing technique....