Browsing by Author "Levent, Mehmet Latif"

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Citation - WoS: 1
Citation - Scopus: 2
Adaptive State Feedback Control Method Based on Recursive Least Squares
(Kauno Technologijos Universitetas, 2022) Levent, Mehmet Latif; Aydoğdu, Ömer
This study revealed an adaptive state feedback control method based on recursive least squares (RLS) that is introduced for a time-varying system to work with high efficiency. Firstly, a system identification block was created that gives the mathematical model of the time-varying system using the input/output data packets of the controller system. Thanks to this block, the system is constantly monitored to update the parameters of the system, which change over time. Linear quadratic regulator (LQR) is renewed according to these updated parameters, and self-adjustment of the system is provided according to the changed system parameters. The Matlab/Simulink state-space model of the variable loaded servo (VLS) system module was obtained for the simulation experiments in this study; then the system was controlled. Moreover, experiments were carried out on the servo control experimental equipment of the virtual simulation laboratories (VSIMLABS). The effectiveness of the proposed new method was observed taking the performance indexes as a reference to obtain the results of the practical application of the proposed method. Regarding the analysis of simulation and experimental results, the proposed approach minimizes the load effect and noise and the system works at high efficiency. © 2022 Kauno Technologijos Universitetas. All rights reserved.
Discrete Time State Estimation With Kalman Filter and Adaptive Lqr Control of a Time Varying Linear System
(2020) Levent, Mehmet Latif; Aydoğdu, Ömer; Yücelbaş, Cüneyt
In this study, a new adaptive controller design was created that compensates for variable load effects and provides high control performance. In the proposed control method, Discrete Time Kalman Filter method (DKF), which estimates system output states, and Discrete Time Linear Quadratic Regulator (DLQR) method, one of the optimal control methods, were used. Although the DLQR control method produces good results when applied to unvarying systems, it cannot provide the desired response in time varying systems because it has no adaptation mechanism. In order to solve this problem, an adaptation mechanism based lyapunov method which has been developed that adapts to different environmental conditions, constantly updating a new state feedback gain matrix value (newK ) and optimal lyapunov adaptation gain values (1 ,2 ,3 ,4 ,5 and6 ) used for system control block such as position (1x ) control, speed (2x ) control and current (3x ) control. In this mechanism, lyapunov adaptation gain initial values were calculated using the Artificial Neural Network (ANN) method as a new approach. Thus, it was aimed to eliminate the variable load effects and to increase the stability of the system. In order to demonstrate the effectiveness of the proposed method, a variable loaded VsimLabs (Virtual Simulation laboratories) servo system was modelled as a time-varying linear system and used in practical implementation and simulation in Matlab-Simulink environment. Based on the experimental results and performance measurements such as Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral time absolute error (ITAE), it was observed that the proposed method increases the system performance and stability by minimizing variable load effect and steady state error.
Citation - WoS: 5
Citation - Scopus: 6
Kalman State Estimation and Lqr Assisted Adaptive Control of a Variable Loaded Servo System
(EOS ASSOC, 2019) Aydoğdu, Ömer; Levent, Mehmet Latif
This study actualized a new hybrid adaptive controller design to increase the control performance of a variable loaded time-varying system. A structure in which LQR and adaptive control work together is proposed. At first, a Kalman filter was designed to estimate the states of the system and used with the LQR control method which is one of the optimal control servo system techniques in constant initial load. Then, for the variable loaded servo (VLS) system, the Lyapunov based adaptive control was added to the LQR control method which was inadequate due to the constant gain parameters. Thus, it was aimed to eliminate the variable load effects and increase the stability of the system. In order to show the effectiveness of the proposed method, a Quanser servo module was used in Matlab-Simulink environment. It is seen from the experimental results and performance measurements that the proposed method increases the system performance and stability by minimizing noise, variable load effect and steady-state error.
Citation - WoS: 2
Citation - Scopus: 2
State Estimation With Reduced-Order Observer and Adaptive-Lqr Control of Time Varying Linear System
(KAUNAS UNIV TECHNOLOGY, 2020) Aydoğdu, Ömer; Levent, Mehmet Latif
In this study, a new controller design was created to increase the control performance of a variable loaded time varying linear system. For this purpose, a state estimation with reduced order observer and adaptive-LQR (Linear-Quadratic Regulator) control structure was offered. Initially, to estimate the states of the system, a reduced-order observer was designed and used with LQR control method that is one of the optimal control techniques in the servo system with initial load. Subsequently, a Lyapunov-based adaptation mechanism was added to the LQR control to provide optimal control for varying loads as a new approach in design. Thus, it was aimed to eliminate the variable load effects and to increase the stability of the system. In order to demonstrate the effectiveness of the proposed method, a variable loaded rotary servo system was modelled as a time-varying linear system and used in simulations in Matlab-Simulink environment. Based on the simulation results and performance measurements, it was observed that the proposed method increases the system performance and stability by minimizing variable load effect.
Zamanla Değişen Bir Sistemin Adaptif Durum Geribeslemelikontrolü
(Konya Teknik Üniversitesi, 2021) Levent, Mehmet Latif; Aydoğdu, Ömer
Bu çalışmada, gürültüden ve bozucu etkilerden arındırılmış doğrusal bir sistemin durum geri beslemeli adaptif kontrolü gerçekleştirilmiştir. Bunun için ilk olarak, ayrık zamanlı kalman filtresi ve indirgenmiş dereceli durum gözleyici kullanılarak sistemin durum değişkenleri tahmin edilmiş, elde edilen bu durumlar kullanılarak sistemin optimal kontrolü Lineer Kuadratik Regülatör (Linear Quadratic Regulator, LQR) metodu ile gerçekleştirilmiştir. LQR kontrol metodunda durum geri besleme kazanç matrisi sabit olduğundan, zamanla değişmeyen sistemlerde optimal kontrol performansı sağlamasına rağmen, zamanla değişen sistemlerde istenilen performansı sağlayamadığı görülmüştür. Bu amaçla zamanla değişen sistemlerin de optimal kontrolü için LQR metodu, Lyapunov tabanlı adaptif bir mekanizma ile desteklenerek adaptif durum geribeslemeli denetleyici yapısı tasarlanmıştır. Böylece sisteme etki eden gürültü ve değişken yük etkileri minimize edilerek, sistem kararlılığı artırılmıştır. Çalışmanın ikinci aşamasında; Yinelemeli En Küçük Kareler (Recursive Least Squares, RLS) tabanlı adaptif durum geribeslemeli kontrol metodu ortaya konulmuştur. Burada ilk olarak denetlenen sistemin giriş/çıkış veri paketlerini kullanarak zamanla değişen sistemin matematiksel modelini veren bir sistem tanılama bloğu oluşturulmuştur. Bu blok sayesinde sistem sürekli izlenerek, zamanla değişen sistemin parametreleri güncellenmektedir. Güncellenen bu parametrelere göre LQR yenilenmekte, böylece değişen sistem parametrelerine göre sistemin kendi kendini ayarlaması sağlanmaktadır. Böylece RLS tabanlı adaptif durum geribeslemeli kontrol yaklaşımı ile zamanla değişen yük etkileri minimize edilmiştir. Çalışmada, simülasyon deneyleri için Değişken Yüklü Servo (Variable Loaded Servo, VLS) sistem modülüne ait Matlab/Simulink durum uzay modeli elde edilmiş ve önerilen yeni yöntemler ile sistem kontrolü gerçekleştirilmiştir. Yapılan deneylerde,önerilen yöntem ile literatürde verilen kalman filtresi, indirgenmiş dereceli gözleyici ve LQR'nin birlikte kullanıldığı yöntem sonuçları karşılaştırılmıştır. Elde edilen sonuçlar performans indeksleri referans alınarak değerlendirildiğinde, önerilen yöntemin, literatürdeki diğer çalışmalara göre gürültüyü, değişken yük etkisini ve sürekli durum hatasını daha iyi minimize ederek sistem performansını ve ararlılığını artırdığı görülmüştür. Ayrıca öne sürülen yöntemlerin pratik uygulama sonuçlarını elde edebilmek amacıyla, Sanal Simülasyon Laboratuvarları (Virtual Simulation laboratories, VSIMLABS) servo kontrol deney donamı üzerinde denemeler yapılmış ve performans indeksleri referans alınarak önerilen yöntemin etkinliği gözlemlemiştir. Elde edilen sonuçlardan simülasyon ve uygulama sonuçlarının uyumlu olduğu görülmektedir. Ayrıca simülasyon ve uygulama sonuçları analiz edildiğinde, öne sürülen yaklaşımın yük etkisini ve gürültüyü minimize ettiğini ve sistemin yüksek verimlilikte çalıştığını göstermiştir.