In this paper, the robust neuro-fuzzy networks (RNFNs) are proposed to improve the problems of neuro-fuzzy networks (NFNs) for modeling with outliers. Firstly, the support vector regression (SVR) approach is applied to obtain the initial structure of RNFNs. Because of the SVR approach is equivalent to solving a linear constrained quadratic programming problem under the fixed structure of SVR, t...

Quad rotor is a renowned underactuated Unmanned Aerial Vehicle (UAV) with widespread military and civilian applications. Despite its simple structure, the vehicle suffers from inherent instability. Therefore, control designers always face formidable challenge in stabilization and control goal. In this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nat...

abstract purpose of this paper: the objectives of this paper are two folds: (1) utilizing hierarchical fuzzy technique for order preference by similarity to ideal solution (topsis) approach to evaluate the most suitable rfid-based systems decision, and (2) to highlight key risks and benefits of radio frequency identification technology in healthcare industry. design/methodology/approach: resear...

ÐA fuzzy decision tree is constructed by allowing the possibility of partial membership of a point in the nodes that make up the tree structure. This extension of its expressive capabilities transforms the decision tree into a powerful functional approximant that incorporates features of connectionist methods, while remaining easily interpretable. Fuzzification is achieved by superimposing a fu...

In this paper, a novel sliding mode control theory-based learning algorithm is proposed to train an interval type-2 fuzzy neural network using type-2 fuzzy triangular membership functions. The structure considered is a type-2 Takagi–Sugeno–Kang fuzzy logic system in which the antecedents are type-2 fuzzy sets, and consequents are crisp numbers (A2-C0). In the proposed learning algorithm, instea...

Mamdani fuzzy models have always been used as black-box models. Their structures in relation to the conventional model structures are unknown. Moreover, there exist no theoretical methods for rigorously judging model stability and validity. I attempt to provide solutions to these issues for a general class of fuzzy models. They use arbitrary continuous input fuzzy sets, arbitrary fuzzy rules, a...

In pH reactors, determination and control of pH is a common problem concerning chemical-based industrial processes due to the non-linearity observed in the titration curve. We introduced a modified multiregional fuzzybased control system to overcome the complexity of precise control of pH. In order to compensate for the experimental inaccuracies in measurements of pH in-situ values; an observer...

This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

in order to have better insight of project characteristics, different kinds of fuzzy analysis for project networks have been recently proposed, most of which consider activities duration as the main and only source of imprecision and vagueness, but as it is usually experienced in real projects, the structure of the network is also subject to changes. in this paper we consider three types of imp...