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Yayın Extremum seeking control of uncertain systems(Işık University Press, 2017) Dinçmen, ErkinExtremum seeking is used in control problems where the reference trajectory or reference set point of the system is not known but it is searched in real time in order to maximize or minimize a performance function representing the optimal behaviour of the system. In this paper, extremum seeking algorithm is applied to the systems with parametric uncertainties.Yayın Neural network steering control algorithm for autonomous ground vehicles having signal time delay(SAGE Publications Ltd, 2024-03) Dinçmen, ErkinAn adaptive neural network–based steering control algorithm is proposed for yaw rate tracking of autonomous ground vehicles with in-vehicle signal time delay. The control system consists of two neural networks: the observer neural network and the controller neural network. The observer neural network adapts itself to the system dynamics during the training phase. Once trained, the observer neural network cooperates with the controller neural network, which constantly adapts itself during the control task. In this way, an adaptive and intelligent control structure is proposed. Through simulation studies, it has been shown that while a proportional-integral-derivative type steering controller fails to perform its control task in case of steering signal delay, the proposed control algorithm manages to adapt itself according to the control problem and achieves reference yaw rate tracking. The robustness of the control algorithm according to the signal delay magnitude has been demonstrated by simulation studies. A rigorous Lyapunov stability analysis of the control algorithm is also presented.Yayın Optimal nonlinear control of two-link flexible arm with adaptive internal model(2005) Doğan, Mustafa; İstefanopulos, YorgoThe control of highly nonlinear multi-link flexible arms is subject to uncertainties caused by backlash, payload changes and external disturbances.Therefore, adaptive and robust control of multi-link flexible arms is a challenging problem.In this paper, the internal model approach is adaptively tuned up for unknown disturbances, parallel with a robust stabilizer. The stabilizer part of the controller is optimized with a new evolutionary algorithm.Yayın A cooperative neural network control structure and its application for systems having dead-zone nonlinearities(Springer International Publishing Ag, 2022-03) Dinçmen, ErkinAn adaptive control structure utilizing two feed-forward neural networks (NN) is proposed to deal with systems having unknown nonlinearities. One of the networks is trained to mimic the nonlinear system dynamics. Its training will be repeated with periods in order to keep it an updated valid model of the system all the times since the parameters and/or nonlinearities of the system may change during time. The other network, which is the Controller NN, adapts itself continuously by collaborating with the Model NN. The stability-convergence analysis of both networks is performed via Lyapunov method. An example system is chosen to show the applicability of the control algorithm. This example system is created by combining a linear dynamics model with a dead-zone function to represent a nonlinear system to be controlled. It should be noted that the proposed control structure can be used in any nonlinear system without knowing the system dynamics. The only information required by Model NN is the training set consisting input-output data pairs of the system. The Model NN is trained offline with this training set, and afterward the Controller NN adapts its weights online continuously during the control task with the help of Model NN. The performances of PD and PID controllers are also given for comparison purposes.Yayın Modelling and simulation studies on adaptive controller for alt-azimuth telescopes despite unknown wind disturbance and mass(SAGE Publications, 2020-09-15) Keskin, Onur; Ünal, Ali Cem; Kararsız, Gökhan; Yılmaz, Tuğrul; Yeşilyaprak, CahitNumerous ground-based observatories are using small sized ground telescopes for scientific research purposes. The telescopes that are available on the market have three main problems. These issues can be listed as: positioning repeatability, tuning requirement according to different wind speeds for different seasons, and the mass changing via different scientific equipments added to the telescope. This study is aimed at resolving these issues for ground based small alt-azimuth telescopes. Establishing of a set and forget system is performed by designing an adaptive controller. Motor dynamics are taken into consideration for a realistic mathematical model. The Wind-Gust model that consists of a sum of sinusoidal disturbances with unknown phase, amplitude and frequency is used for the wind model. The purposed controller cancels the disturbance effects on the plant while operational positioning and also the makes the plant insensitive to mass changes. The Lyapunov approach is utilised when proving the asymptotic stability. The proposed controller’s success is illustrated with thorough numerical evaluation.Yayın Adaptive backstepping approach for 2-DOF telescopes despite unknown wind disturbance(Institute of Electrical and Electronics Engineers Inc., 2019-07) Ünal, Ali Cem; Yılmaz, Cemal Tuğrul; Kararsız, Gökhan; Keskin, Onur; Yeşilyaprak, CahitSmall ground telescopes on the marked are widely used in many space observatories and scientific researches. There are three main problems in such telescopes; positioning of the focal point and the need of tuning for both different seasonal wind speeds and mass changes of the telescope arm. This study focuses on eliminating those problems for 2-DOF altazimuth configuration small telescopes. An adaptive controller is designed to create a set and forget system. The mathematical model of the telescope is derived based on RR type joint configuration. For a realistic approach, motor dynamics is considered in the mathematical model. The wind disturbance is modeled according to the Wind-Gust model which is a sum of sinusoidal with unknown amplitude, frequency and phase. The controller aims to cancel the effect of the disturbance on focal point of the telescope while positioning. The asymptotic stability is proven with the Lyapunov approach. The numerical study is illustrated to success of the proposed controller.
