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AK, AYÇA

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End date: 2023 × Subject: Fuzzy logic ×

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    PublicationOpen Access
    Integral fuzzy sliding mode controller for hydraulic system using neural network modelling
    (2023-08-01) AK, AYÇA; AK A., Yılmaz E., Katrancıoğlu S.
    In this paper, a hydraulic motor controller is designed with a fuzzy supported integral sliding mode algorithm. The hydraulic system used in the study was modeled using artificial neural networks. Ability of handling nonlinearity of systems makes sliding mode controller to be a good choose for this system. It is thought that the robustness of the system against uncertainties can be achieved with the help of an integral sliding mode controller. The basic concept of the suggested control method is to use fuzzy logic for adaptation of the integral sliding mode control switching gain. Such adjustment reduces the chattering that is the most problem of classical sliding mode control. The equivalent control is computed with utilizing the radial basis function neural network. The simulation results of the presented method are compared with the results of the PID controller whose parameters were obtained by means of a genetic algorithm (GA) and particle swarm optimization (PSO). It proved that it is more efficient to control the hydraulic system with integral fuzzy sliding mode control using neural network.
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    SMC controller design for DC motor speed control applications and performance comparison with FLC, PID and PI controllers
    (2023-01-01) AK, AYÇA; Rahmatullah R., AK A., serteller N. F. O.
    Sliding Mode Control (SMC), which is built on the variable structure control (VSC) algorithm, is a robust and non-linear control method that can provide the desired dynamic behaviour for the system to be controlled despite external and internal disturbances and uncertainties. The SMC method can be successfully implemented in the control of high-dimensional nonlinear systems operating under uncertain conditions due to its high accuracy and simplicity of application. In this MATLAB/Simulink based study; the SMC method is applied to the speed control of a DC motor. For this purpose, firstly, the dynamic model of DC motor and the mathematical model of the SMC have been designed and transferred to the Simulink environment. The performance of the SMC system has been examined under different loading conditions applied to the motor. In addition, the effects of changing the SMC parameters on the sliding surface, chattering and motor dynamic behaviours have been investigated. In order to evaluate the success of the SMC topology in DC motor control application, Fuzzy Logic Control, PID and PI control methods were applied on the same motor and their performances were compared with the SMC method.