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A defuzzification based new algorithm for the design of Mamdani-type fuzzy controllers

Jean Jamil Saade (2000)

Mathware and Soft Computing

This paper presents a new learning algorithm for the design of Mamdani- type or fully-linguistic fuzzy controllers based on available input-output data. It relies on the use of a previously introduced parametrized defuzzification strategy. The learning scheme is supported by an investigated property of the defuzzification method. In addition, the algorithm is tested by considering a typical non-linear function that has been adopted in a number of published research articles. The test stresses on...

A fuzzy if-then rule-based nonlinear classifier

Jacek Łęski (2003)

International Journal of Applied Mathematics and Computer Science

This paper introduces a new classifier design method that is based on a modification of the classical Ho-Kashyap procedure. The proposed method uses the absolute error, rather than the squared error, to design a linear classifier. Additionally, easy control of the generalization ability and robustness to outliers are obtained. Next, an extension to a nonlinear classifier by the mixture-of-experts technique is presented. Each expert is represented by a fuzzy if-then rule in the Takagi-Sugeno-Kang...

A fuzzy nonparametric Shewhart chart based on the bootstrap approach

Dabuxilatu Wang, Olgierd Hryniewicz (2015)

International Journal of Applied Mathematics and Computer Science

In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value). Usually fuzzy data (described by fuzzy random variables) do not have a distributional model available, and also the size of the fuzzy sample data is small. Based on the bootstrap methodology, we design a nonparametric Shewhart control chart in the space of fuzzy random variables equipped with some L2 metric, in which a novel...

A fuzzy system with ε-insensitive learning of premises and consequences of if-then rules

Jacek Łęski, Tomasz Czogała (2005)

International Journal of Applied Mathematics and Computer Science

First, a fuzzy system based on ifFirst, a fuzzy system based on if-then rules and with parametric consequences is recalled. Then, it is shown that the globalthen rules and with parametric consequences is recalled. Then, it is shown that the global and local ε-insensitive learning of the above fuzzy system may be presented as a combination of both an ε-insensitive gradient method and solving a system of linear inequalities. Examples are given of using the introduced method to design fuzzy models...

A new fuzzy Lyapunov approach to non-quadratic stabilization of Takagi-Sugeno fuzzy models

Ibtissem Abdelmalek, Noureddine Goléa, Mohamed Hadjili (2007)

International Journal of Applied Mathematics and Computer Science

In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we propose are less conservative and stabilize also fuzzy systems which do not admit a quadratic stabilization....

A novel LMI-based robust model predictive control for DFIG-based wind energy conversion systems

Amir Gholami, Alireza Sahab, Abdolreza Tavakoli, Behnam Alizadeh (2019)


The optimal and reliable performance of doubly fed induction generator is essential for the efficient and optimal operation of wind energy conversion systems. This paper considers the nonlinear dynamic of a DFIG linked to a power grid and presents a new robust model predictive control technique of active and reactive power by the use of the linear matrix inequality in DFIG-based WECS. The control law is obtained through the LMI-based model predictive control that allows considering both economic...

A situation-based multi-agent architecture for handling misunderstandings in interactions

Thao Phuong Pham, Mourad Rabah, Pascal Estraillier (2015)

International Journal of Applied Mathematics and Computer Science

During interactions, system actors may face up misunderstandings when their local states contain inconsistent data about the same fact. Misunderstandings in interactions are likely to reduce interactivity performances (deviation or deadlock) or even affect overall system behavior. In this paper, we characterize misunderstandings in interactions between system actors (that may be human users or system agents) in interactive adaptive systems. To deal with such misunderstandings and ensure state consistency,...

Adaptive control of cluster-based Web systems using neuro-fuzzy models

Krzysztof Zatwarnicki (2012)

International Journal of Applied Mathematics and Computer Science

A significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems using neuro-fuzzy...

An example of the knowledge based controller-design and evaluation.

Oto Tezak (1999)

Mathware and Soft Computing

Knowledge based controller for a balance control model is presented in this paper. The design of the controller was based on the human control of the same process. Developed controller is tested by means of simulation and operation on the laboratory balance control model. The simulation results of the controller as well as a statistical description of the experiments with developed controller and human control is presented in the paper. Verification is based on experiments with an intelligent controller...

Automatic risk control based on FSA methodology adaptation for safety assessment in intelligent buildings

Jerzy Mikulik, Mirosław Zajdel (2009)

International Journal of Applied Mathematics and Computer Science

The main area which Formal Safety Assessment (FSA) methodology was created for is maritime safety. Its model presents quantitative risk estimation and takes detailed information about accident characteristics into account. Nowadays, it is broadly used in shipping navigation around the world. It has already been shown that FSA can be widely used for the assessment of pilotage safety. On the basis of analysis and conclusion on the FSA approach, this paper attempts to show that the adaptation of this...

Beta fuzzy logic systems approximation properties in the mimo case

Adel Alimi, Radhia Hassine, Mohamed Selmi (2003)

International Journal of Applied Mathematics and Computer Science

Many researches have been interested in the approximation properties of Fuzzy Logic Systems (FLS), which, like neural networks, can be seen as approximation schemes. Almost all of them tackled the Mamdani fuzzy model, which was shown to have many interesting approximation features. However, only in few cases the Sugeno fuzzy model was considered. In this paper, we are interested in the zero-order Multi-Input-Multi-Output (MIMO) Sugeno fuzzy model with Beta membership functions. This leads to Beta...

Comparative analysis of noise robustness of type 2 fuzzy logic controllers

Emanuel Ontiveros-Robles, Patricia Melin, Oscar Castillo (2018)


Nowadays Fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic approach, allows managing uncertainty in the model. Type-2 Fuzzy Logic has recently shown to provide significant improvement in image processing applications, however it is also important to analyze its impact in controller performance. This paper is presenting a comparison in the robustness of Interval Type-2 and Generalized...

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