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Article Citation - WoS: 40Citation - Scopus: 52Variable Structure Control of a Class of Uncertain Systems(Pergamon-elsevier Science Ltd, 2004) Efe, MÖ; Ünsal, C; Kaynak, O; Yu, XHThis brief paper proposes a method for tuning the parameters of a variable structure controller. The approach presented extracts the error at the output of the controller and applies a nonlinear tuning law using this error measure. The adaptation mechanism drives the state tracking error vector to the sliding hypersurface and maintains the sliding mode. In the simulations, the approach presented has been tested on the control of Dulling oscillator and the analytical claims have been justified under the existence of measurement noise, uncertainty and large nonzero initial errors. (C) 2003 Elsevier Ltd. All rights reserved.Article Citation - WoS: 1Citation - Scopus: 3Multivariable Nonlinear Model Reference Control of Cement Mills(Arnold, Hodder Headline Plc, 2003) Efe, MÖ; Department of Electrical & Electronics EngineeringThis paper presents a method for model reference control of a cement milling circuit that has previously been studied several times. The approach presented is based on an experimentally justified model of a cement milling circuit. We derive the form of the control vector with the goal of driving the response of the system to that of a desired model in a noisy operating environment. The paper demonstrates the selection of the reference dynamics and the derivation of the control laws. The approach is based on the Lyapunov theory, and the results observed justify the tracking and stability claims of the paper.Article Citation - WoS: 1Citation - Scopus: 3A robust on-line learning algorithm for intelligent control systems(John Wiley & Sons Ltd, 2003) Efe, MÖ; Kaynak, O; Wilamowski, BM; Yu, XHThis paper describes a novel error extraction approach for exploiting the strength of Levenberg-Marquardt (LM) optimization technique in intelligent control systems: Since the target value of the control signal is unknown, tuning of the controller parameters becomes a tedious task if the knowledge about the system and the environment is limited. The suggested methodology utilizes the sliding model control (SMC) technique. The error extraction scheme postulates the form of error on the applied control signal using the discrepancy from the prescribed reaching dynamics. The devised approach has been tested on the non-linear Duffing oscillator, which has been forced to follow a periodic orbit radically different from the natural one. The results obtained through a series of simulations have confirmed the high precision and robustness advantages without knowing the analytical details of the system under investigation. The issues of observation noise and the stability in the parametric space have approximately been addressed from the point of SMC perspective. Copyright (C) 2003 John Wiley Sons, Ltd.Article Citation - WoS: 4Citation - Scopus: 4Multi Input Dynamical Modeling of Heat Flow With Uncertain Diffusivity Parameter(Taylor & Francis inc, 2003) Efe, MÖ; Özbay, HThis paper focuses on the multi-input dynamical modeling of one-dimensional heat conduction process with uncertainty on thermal diffusivity parameter. Singular value decomposition is used to extract the most significant modes. The results of the spatiotemporal decomposition have been used in cooperation with Galerkin projection to obtain the set of ordinary differential equations, the solution of which synthesizes the temporal variables. The spatial properties have been generalized through a series of test cases and a low order model has been obtained. Since the value of the thermal diffusivity parameter is not known perfectly, the obtained model contains uncertainty. The paper describes how the uncertainty is modeled and how the boundary conditions are separated from the remaining terms of the dynamical equations. The results have been compared with those obtained through analytic solution.
