4th International Conference on Intelligent and Fuzzy Systems (INFUS), Bornova, Turkey, 19 - 21 July 2022, vol.504, pp.752-760
This paper aims to design deep recurrent neural network controllers for linear and non-linear systems. Design and comparison with two different controllers are considered. A pure recurrent neural network controller and self-tuning PID controller based on recurrent neural networks (PRNN), according to the influence of the object's parameter on system output performance, The PRNN can auto-adjust its weights to vary k(P), k(I) and k(D) The emulation results show that the presented control systems have quick response speed and strong adaptive capability.