Journal ArticleDOI
Neural adaptive tracking control of a DC motor
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TLDR
It is shown that, through the proposed control scheme, the rotor speed or position of a DC motor can follow any arbitrarily selected trajectories under variable load torque.About:
This article is published in Information Sciences.The article was published on 1999-09-01. It has received 97 citations till now. The article focuses on the topics: Adaptive control & Sliding mode control.read more
Citations
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Journal ArticleDOI
Time-series forecasting using flexible neural tree model
TL;DR: This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT), which is generated initially as a flexible multi-layer feed-forward neural network and evolved using an evolutionary procedure.
Journal Article
Time-series forecasting using flexible neural tree model
TL;DR: In this paper, a new time-series forecasting model based on the flexible neural tree (FNT) is introduced. But the model is not suitable for time series forecasting and it is difficult to select the proper input variables or time-lags for constructing a time series model.
Journal ArticleDOI
Sliding mode control with PID sliding surface and experimental application to an electromechanical plant.
TL;DR: Experimental results that are compared with the results of conventional PID verify that the proposed sliding mode controller can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances.
Journal ArticleDOI
Nonlinear modeling and identification of a DC motor for bidirectional operation with real time experiments
Tolgay Kara,İlyas Eker +1 more
TL;DR: In this paper, the Hammerstein nonlinear system approach is used for identification of a DC motor rotating in two directions with real-time experiments, and the major nonlinearities, such as Coulomb friction and dead zone, are investigated and integrated in the nonlinear model.
Journal ArticleDOI
A Derivative-Free Kalman Filtering Approach to State Estimation-Based Control of Nonlinear Systems
TL;DR: The proposed derivative-free Kalman filtering approach is suitable for state estimation-based control of a class of nonlinear systems without the need for derivatives and Jacobians calculation and without using linearization approximations.
References
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Book
Applied Nonlinear Control
TL;DR: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
Book
Nonlinear Control Systems
Alberto Isidori,M. Thoma,Eduardo D. Sontag,B. W. Dickinson,A. Fettweis,J. L. Massey,J. W. Modestino +6 more
TL;DR: In this paper, a systematic feedback design theory for solving the problems of asymptotic tracking and disturbance rejection for linear distributed parameter systems is presented, which is intended to support the development of flight controllers for increasing the high angle of attack or high agility capabilities of existing and future generations of aircraft.
Book
Adaptive Control: Stability, Convergence and Robustness
S. Shankar Sastry,Marc Bodson +1 more
TL;DR: In this paper, the deterministic theory of adaptive control (AC) is presented in an introduction for graduate students and practicing engineers, with a focus on basic AC approaches, notation and fundamental theorems, identification problem, model-reference AC, parameter convergence using averaging techniques, and robustness.
Book
Feedback Systems: Input-output Properties
TL;DR: In this paper, the Bellman-Gronwall Lemma has been applied to the small gain theorem in the context of linear systems and convolutional neural networks, and it has been shown that it can be applied to linear systems.
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