Browsing by Author "Jafari, Reza"

Now showing 1 - 7 of 7
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    Box-Jenkins Model of Elastic Drive System Using Levenberg-Marquardt Algorithm
    Jafari, Reza (Springer Nature, 2024-03-21)
    This paper explains the derivation of Box-Jenkins model for the elastic drive system using Levenberg-Marduardt algorithm. The Box-Jenkins model which is the most flexible linear model has been chosen to identify the elastic drive system. The GPAC analysis has been used for the preliminary identification and the Maximum Likelihood Estimator (Levenberg-Marduardt) is used for the parameter estimations. Several models have been developed for the elastic drive system and the simplest model has been chosen. The accuracy of the final model, residual analysis, has been checked using CHI-Square test.
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    Enhanced precision in robot arm positioning: A nonlinear damping approach for flexible joint manipulators
    Jafari, Amir Hossein; Dhaouadi, Rached; Jafari, Reza (Wiley, 2024-06-22)
    This article introduces an advanced nonlinear controller designed for optimizing the performance of a single‐link robot arm featuring a flexible joint. The proposed nonlinear control strategy incorporates a Proportional‐Integral (PI) controller in conjunction with a nonlinear velocity feedback component, aimed at providing effective nonlinear damping and suppressing vibrations. To validate the controller's performance, extensive simulations are conducted utilizing machine learning techniques within the Python environment. The performance of the proposed nonlinear damping controller is benchmarked against a conventional linear cascaded P‐PI control structure, with both controllers fine‐tuned using the Nelder‐Mead algorithm. Simulation results demonstrate that the nonlinear damping controller yields substantial improvements in the dynamic behavior of the robot axis arm, showcasing superior step and sinusoidal position tracking performance, along with active vibration damping capabilities. This research contributes valuable insights into the enhanced nonlinear control strategies for flexible‐joint robot arms, offering promising advancements in their overall dynamic performance.
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    Forward and Converse Lyapunov Theorems for Discrete Dynamical Systems
    Jafari, Reza; Kable, Anthony; Hagan, Martin (IEEE, 2014-08-20)
    This paper derives the necessary and sufficient conditions for the Lyapunov function such that the equilibrium point of a dynamical system is stable or Globally Asymptotic Stable (GAS). The paper shows that continuity of Lyapunov function at the equilibrium point is the only necessary and sufficient condition for stability. We shows that a certain type of converse theorem can not be proved with continuous Lyapunov function. The Tower of Babel ‘TOB’ is given as an example of stable dynamical system in which no continuous Lyapunov function exists for this system.
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    Global stability analysis using the method of Reduction Of Dissipativity Domain
    Jafari, Reza; Hagan, Martin (IEEE, 2011-07)
    This paper describes a modification to the method of Reduction Of Dissipativity Domain with Linear Boundaries (RODD-LB1) which was introduced by Barabanov and Prokharov [7]. The RODD method is a computational technique for the global stability analysis of nonlinear dynamic systems. In this paper we introduce an extension to the original RODD method that is designed to speed up convergence. The efficiency of the extended algorithm is demonstrated through numerical examples.
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    Nonlinear Adaptive control with High-Gain Observer
    Jafari, Reza (2025-06-30)
    In this paper we present an adaptive nonlinear output feedback controller with high-gain observer. One of the main challenge with the design of nonlinear adaptive controller is the stability concern. The stability analysis of the overall closed loop system is addressed through the Lyapunov theorem. The performance of the proposed controller with high-gain observer is tested on a single manipulator with flexible joints.
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    Speech Recognition Using ARMA Model and Levenberg-Marquardt Algorithm
    Jafari, Reza; Jafari, Amir H. (Springer, 2024-08-01)
    Autoregressive Moving Average (ARMA) is a simple linear model with memory that can be used for speech recognition problems. This is why, this paper utilized the derivation of ARMA model for the speech recognition. The flexibility of ARMA model helps in derivation of an accurate model that recognizes the pronunciation of letter B. The Generalized Partial Autocorrelation (GPAC) analysis has been used for the preliminary identification and the Maximum Likelihood Estimator (Levenberg-Marquardt) is used for the parameter estimations. Several models have been developed to recognize the letter B that are pronounced by a lady 30 times. The simplest model has been chosen at the end. The accuracy of the final model has been checked using χ2 test.
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    Stability Analysis of Recurrent-Neural-Based Controllers Using Dissipativity Domain
    Jafari, Reza (MDPI, 2023-07-10)
    This paper proposes a method for the stability analysis of dynamic neural networks. The stability analysis of dynamic neural networks is a challenging task due to internal feedback connections. In this research work, we propose an algorithm based on the Reduction of Dissipativity Domain (RODD) algorithm. The RODD algorithm is a numerical technique for the detection of the stability of nonlinear dynamic systems. The method works by using an approximation of the reachable set. This paper proposes linear and quadratic approximations of reachable sets. RODD-LB uses a linear approximation, RODD-EB uses a quadratic approximation, and the RODD-Hybrid algorithm uses a combination of the linear and quadratic approximations. The accuracy and convergence of these algorithms were derived through numerical dynamic systems.