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- MakaleAçık Erişim2025Scopus SJRQ2Lyapunov-based adaptive state-space controller for liquid level control of a coupled tank system with unknown model
Lotfieghlim, Armin; Sekban, Hayriye Tuğba; Başçi, Abdullah
In this paper, a Lyapunov-based adaptive state space controller is designed to realize liquid level control in a coupled tank system. The proposed controller is a kind of adaptive control system that combines the principles of state space representation with Lyapunov stability theory to estimate unknown parameters and control a dynamic system. This approach ensures that the system remains stable even when the exact model parameters are unknown or change over time. Moreover, in order to test the performance of the proposed controller, proportional integral (PI) + feedforward (FF) controller is also applied to the same system under the same conditions and the results are compared. The results show that the proposed controller outperforms the PI + FF controller in terms of system response parameters such as rise time, percent overshoot, and settling time. On the other hand, when the error performance metrics integral squared error (ISE), integral time-weighted squared error (ITSE), integral time-weighted absolute error (ITAE), and integral absolute error (IAE) are evaluated, it is seen that the same situation is also realized here, and the proposed controller follows the reference signals with lower error values in real-time studies for different reference signals.
- MakaleYayıncıda açık erişim2023Scopus SJRQ1Designing New Model-Based Adaptive Sliding Mode Controllers for Trajectory Tracking Control of an Unmanned Ground Vehicle
Sekban, Hayriye Tugba; Basci, Abdullah
This paper proposes three new dynamic model-based adaptive sliding mode controllers (ASMC) for trajectory tracking control of unmanned ground vehicles (UGV). The controllers combine kinematic and dynamic control to achieve asymptotic stability and finite-time convergence and their stability is verified using the Lyapunov stability theory. The controllers are designed to address the challenges posed by uncertainties in vehicle dynamic parameters and outperform the sliding mode control (SMC) method in trajectory tracking control. The simulation results of the proposed controllers are also discussed in terms of performance metrics. The simulation results show that the controller proposed in rule 1 shows the better performance in terms of trajectory tracking, and then the controllers proposed in rules 2 and 3 have good performances, respectively. In addition, when the simulation results are compared, it is seen that the performance of all three proposed controllers is better than the SMC.
AtıfScopus12WoS10OpenAlex13
İncele - MakaleYalnız künye2018Scopus SJRQ3Real-time implementation of self-tuning regulator control technique for coupled tank industrial process system
Ayten, Kagan Koray; Dumlu, Ahmet; Kaleli, Aliriza
This article presents the self-tuning regulator control technique for a coupled tank liquid level system that often used in industry. An autoregressive with exogenous model has been used as the liquid process model with the self-tuning control implementation in order to track the desired tank level trajectories with disturbances and uncertainties of the system dynamics. The designed self-tuning controller has been sensitive to parameter variations of the nonlinear coupled tank system. The parameters of the proposed controller are periodically updated themselves during the process by means of online recursive least square method with the forgetting factor algorithm. In this way, the parameter variations and unwanted disturbances of the system are eliminated in real-time application. In order to demonstrate the efficiency of the self-tuning regulator control technique, the real-time studies have been executed. The obtained experimental results demonstrated that the proposed controller gives the better trajectory tracking performance and smaller magnitude in overshot and undershot than the designed classical proportional–integral and sliding mode controllers.
AtıfScopus11WoS5OpenAlex10İncele