Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 6Citation - Scopus: 7Neural Network Based Robust Control of an Aircraft(ACTA Press, 2020) Tanyer, İlker; Tatlıcıoğlu, Enver; Zergeroǧlu, ErkanOutput tracking control of an aircraft subject to uncertainties in the dynamic model and additive state-dependent nonlinear disturbancelike terms is aimed. Uncertainties in the aircraft dynamic model yield an uncertain input gain matrix, which is neither positive definite nor symmetric and an uncertain term in the error dynamics. To deal with the uncertain input gain matrix, a decomposition method is utilized to put error dynamics in a form where an uncertain positive definite matrix multiplies the auxiliary error but this results in the control input to be pre-multiplied first with a unity upper triangular matrix which is uncertain and then with a known diagonal matrix. A novel controller composed of a neural network compensation term and an integral of signum of error is designed. A novel Lyapunov type stability analysis is utilized to prove global asymptotic tracking of output of a reference model. Extensive numerical simulations are presented to demonstrate the efficacy of the proposed controller where robustness to variation of initial states and a comparison with a robust controller are also shown. © 2020 Acta Press. All rights reserved.Conference Object Citation - WoS: 23Citation - Scopus: 23A self tuning RISE controller formulation(Institute of Electrical and Electronics Engineers Inc., 2014) Bıdıklı, Barış; Tatlıcıoğlu, Enver; Zergeroğlu, ErkanIn recent years, controller formulations using robust integral of sign of error (RISE) type feedback have been successfully applied to a variety of nonlinear dynamical systems. The drawback of these type of controllers however, are (i) the need of prior knowledge of the upper bounds of the system uncertainties and (ii) the absence of a proper gain tuning methodology. To tackle the aforementioned weaknesses, in our previous work [1] we have presented a RISE formulation with a time-varying compensation gain to cope for the need of upper bound of the uncertain system. In this study, we have extended our previous design to obtain a fully self tuning RISE feedback formulation. Lyapunov based arguments are applied to prove overall system stability and extensive numerical simulation studies are presented to illustrate the performance of the proposed method. © 2014 American Automatic Control Council.Conference Object Citation - WoS: 7Citation - Scopus: 12Adaptive Actuator Failure Compensation for Redundant Manipulators(Cambridge University Press, 2009) Keçeci, Emin Faruk; Tang, Xidong; Tao, GangThis paper presents an adaptive actuator failure compensation method, which compensates for uncertainties due to unknown actuator failures for redundant manipulator systems. The method is first developed for manipulators whose joints are concurrently actuated. While physical realization of concurrently actuated manipulators and the advantages of their use have been understood before, in this paper failure modeling, controller structure, and adaptive update rules for handling uncertainties from the actuator failures are studied. The adaptive actuator failure compensation method is then expanded for a cooperating multiple manipulator system with uncertain actuator failures. Dynamic equations of such a multiple manipulator system in the task space are derived and the adaptive actuator failure compensation problem is formulated in the task space, for which a compensation controller structure is proposed with stable adaptive parameter update laws. The adaptive control scheme is able to compensate for the uncertainties of system parameters and actuator failures in a more general sense. For both cases, closed-loop system stability and asymptotic tracking are proved, despite uncertain system failures.