Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Subject: search.filters.subject.Lyapunov methodsWoS Q: search.filters.wosQuartile.Q1

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Now showing 1 - 5 of 5
  • Article
    Citation - WoS: 39
    Citation - Scopus: 43
    Self-Adjusting Fuzzy Logic Based Control of Robot Manipulators in Task Space
    (Institute of Electrical and Electronics Engineers Inc., 2021) Yılmaz, Bayram Melih; Tatlıcıoğlu, Enver; Savran, Aydoğan; Alcı, Musa
    End effector tracking control of robot manipulators subject to dynamical uncertainties is the main objective of this work. Direct task space control that aims minimizing the end effector tracking error directly is preferred. In the open loop error system, the vector that depends on uncertain dynamical terms is modeled via a fuzzy logic network and a self-adjusting adaptive fuzzy logic component is designed as part of the nonlinear proportional derivative based control input torque. The stability of the closed loop system is investigated via Lyapunov based arguments and practical tracking is proven. The viability of the proposed control strategy is shown with experimental results. Extensions to uncertain Jacobian case and kinematically redundant robots are also presented. IEEE
  • Article
    Citation - WoS: 11
    Citation - Scopus: 11
    Model Reference Tracking Control of an Aircraft: a Robust Adaptive Approach
    (Taylor and Francis Ltd., 2017) Tanyer, İlker; Tatlıcıoğlu, Enver; Zergeroğlu, Erkan
    This work presents the design and the corresponding analysis of a nonlinear robust adaptive controller for model reference tracking of an aircraft that has parametric uncertainties in its system matrices and additive state- and/or time-dependent nonlinear disturbance-like terms in its dynamics. Specifically, robust integral of the sign of the error feedback term and an adaptive term is fused with a proportional integral controller. Lyapunov-based stability analysis techniques are utilised to prove global asymptotic convergence of the output tracking error. Extensive numerical simulations are presented to illustrate the performance of the proposed robust adaptive controller.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 5
    An Asymptotically Stable Robust Controller Formulation for a Class of Mimo Nonlinear Systems With Uncertain Dynamics
    (Taylor and Francis Ltd., 2016) Bıdıklı, Barış; Tatlıcıoğlu, Enver; Zergeroğlu, Erkan; Bayrak, Alper
    In this work, we present a novel continuous robust controller for a class of multi-input/multi-output nonlinear systems that contains unstructured uncertainties in their drift vectors and input matrices. The proposed controller compensates uncertainties in the system dynamics and achieves asymptotic tracking while requiring only the knowledge of the sign of the leading principal minors of the input gain matrix. A Lyapunov-based argument backed up with an integral inequality is applied to prove the asymptotic stability of the closed-loop system. Simulation results are presented to illustrate the viability of the proposed method.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 9
    Range Identification for Nonlinear Parameterizable Paracatadioptric Systems
    (Elsevier Ltd., 2010) Nath,N.; Tatlicioglu,E.; Dawson,D.M.
    In this paper, a new range identification technique for a calibrated paracatadioptric system mounted on a moving platform is developed to recover the range information and the three-dimensional (3D) Euclidean coordinates of a static object feature. The position of the moving platform is assumed to be measurable. To identify the unknown range, first, a function of the projected pixel coordinates is related to the unknown 3D Euclidean coordinates of an object feature. This function is nonlinearly parameterized (i.e., the unknown parameters appear nonlinearly in the parameterized model). An adaptive estimator based on a minmax algorithm is then designed to estimate the unknown 3D Euclidean coordinates of an object feature relative to a fixed reference frame which facilitates the identification of range. A Lyapunov-type stability analysis is used to show that the developed estimator provides an estimation of the unknown parameters within a desired precision. Numerical simulation results are presented to illustrate the effectiveness of the proposed range estimation technique. © 2010 Elsevier Ltd. All rights reserved.
  • Conference Object
    Citation - Scopus: 1
    Range Identification for Nonlinear Parameterizable Paracatadioptric Systems
    (Institute of Electrical and Electronics Engineers Inc., 2009) Nath, Nitendra; Dawson, Darren M.; Tatlıcıoğlu, Enver
    In this paper, a new range identification technique for a calibrated paracatadioptric system mounted on a moving platform is developed to recover the range information and the three-dimensional (3D) Euclidean coordinates of a static object feature. The position of the moving platform is assumed to be measurable. To identify the unknown range, first a function of the projected pixel coordinates is related to the unknown 3D Euclidean coordinates of an object feature. This function is nonlinearly parameterized (i.e., the unknown parameters appear nonlinearly in the parameterized model). An adaptive estimator based on a min-max algorithm is then designed to estimate the unknown 3D Euclidean coordinates of an object feature relative to a fixed reference frame which facilitates the identification of range. A Lyapunov-type stability analysis is used to show that the developed estimator provides an estimation of the unknown parameters within a desired precision.