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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...
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...
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...
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...
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....
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...
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,...
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...
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...
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...
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...
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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