Özet:

This article provides a study aimed at adjusting the ratings of the adaptive cutting-degree PID (FOPID) controller using artificial nerve networks (YSA). Adaptive adjustment of the controller ratings is very important for durability in practical control applications. Because due to parameters uncertainty and external factors, the change of system ratings can negatively affect the controller's resilience. In this study, the YSA and the controller’s proportional, integral and derivative earnings ratings can be re-adjusted according to the condition while the control process continues. This also provides an adaptive and dynamic structure to the cut-grade PID controller. In the classical control applications, the earnings rates are initially adjusted by the designer and remain stable during the control period, not changing. However, in today’s control practices, these types of controls remain insufficient. The YSAs, after being trained, set the controller’s earnings ratings in the best way. Thanks to refuels, they improve the controller’s performance by reducing the error. If the parameters of the controlled system are deteriorated during the control process, the YSAs will automatically re-adjust the controller ratings to the optimal value. The recommended method facilitates the applicability of the FOPID controller for practical control applications. The design of FOPI, FOPD, FOPID controllers containing YSA using MATLAB/Simulink to show the performance of the recommended adaptive control method in two simulation examples has been carried out and unit step-by-step answers have been presented.

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