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.

In this paper, speed control of a DC Motor with time varying loaded is performed by using sliding mode control (SMC), classical PID control and iterative learning control (ILC) methods. SMC is a robust nonlinear control method which has insensibility against to external disturbing effects and parametric variations of system. On the other hand, a control method of ILC provides an excellent performance on tracking. In the iterative learning PID (IL-PID) controller, the parameters of PID are automatically adjusted by using the algorithm of iterative learning. In this study, firstly, a DC Motor is modeled by using real data. Secondly, controllers which are an iterative learning PID (IL-PID), SMC-based and classical PID are designed and tested. Moreover, performance analysis of these controllers is done for load changes in the time interval. According to obtained results, the output of SMCbased system converges quickly to the reference value and the system gives the fastest response when changing of load occurs. Another result of this study is that the steady state error based on the learning success of ILC is decreased by IL-PID controller. The novel part of this study is that the comparison of these types of controllers is firstly made with this study. 

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.

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.

hesaplanmıştır. Böylece değişken yük etkilerinin minimize edilmesi ve sistem kararlılığının artırılması amaçlanmıştır. Önerilen yöntemin etkinliğini pratik uygulama ve simülasyonda göstermek için, zamanla değişen doğrusal bir sistem olan değişken yüklü bir Sanal Simülasyon laboratuvarları (Virtual Simulation Laboratories, VsimLabs) servo sistemi modellenmiş ve Matlab Simulink ortamında kullanılmıştır. Deneysel sonuçlara ve İntegral Karesel Hata (Integral Square Error, ISE), İntegral Mutlak Hata (Integral Absolute Error, IAE), İntegral Zamanlı Mutlak Hata (Integral time absolute error, ITAE) gibi performans ölçümlerine göre, önerilen yöntemin değişken yük etkisini ve sürekli durum hatasını minimize ederek sistem performans ve kararlılığını artırdığı görülmüştür.