In this study, we develop fuzzy adaptive tracking control via two-layer fuzzy observers, variable structure systems (VSS), and H∞ control algorithm for nonlinear systems with plant uncertainties, output delays, and external disturbances. The Takagi–Sugeno fuzzy dynamic model with adaptation capability is used to approximate the nonlinear system. When the system states are not available, the sta...

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of the fuzzy set theory, especially in the realm of the industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the inputoutput relations i.e., accurate mathematical models. The fuzzy...

Article history: Received 20 February 2011 Accepted 4 April 2011 Available online xxxx

Maintenance plays now a critical role in manufacturing for achieving important cost savings and competitive advantage while preserving product conditions. It suggests moving from conventional maintenance practices to predictive strategy. Indeed the maintenance action has to be done at the right time based on the system performance and component Remaining Useful Life (RUL) assessed by a prognost...

Electrical conductivity is an important indicator for water quality assessment. Since the composition of mineral salts affects the electrical conductivity of groundwater, it is important to understand the relationships between mineral salt composition and electrical conductivity. In this present paper, we develop an adaptive neuro-fuzzy inference system (ANFIS) model for groundwater electrical ...

A fuzzy sliding-mode control with rule adaptation design approach with decoupling method is proposed. It provides a simple way to achieve asymptotic stability by a decoupling method for a class of uncertain nonlinear systems. The adaptive fuzzy sliding-mode control system is composed of a fuzzy controller and a compensation controller. The fuzzy controller is the main rule regulation controller...

In this paper, an adaptive H interval type-2 fuzzy controller is proposed for a class of unknown nonlinear discrete-time systems with training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 fuzzy control scheme and H control approach are incorporated to implement the main objective of controlling the plant to track a reference trajectory....

In this paper, a novel state error feedback sliding controller is proposed. In the controller, an optimal feedback gain is required and in this study it is assumed to be unknown. Usually, a rudimentary feedback gain is used. Besides, in order to approximate the state error feedback sliding controller with the optimal feedback gain, an adaptive fuzzy system is employed. Thus, the proposed contro...

This paper assesses the operator functional state (OFS) based on a collection of psychophysiological (i.e., cardiovascular and EEG) and performance measures. Two types of adaptive fuzzy model, namely ANFIS (adaptivenetwork-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved ...