This paper describes an intelligent adaptive PID controller design procedure. The controller consists of a discrete time PID and an auto-tuning neural network unit. First system identification with a nonlinear autoregressive model (NARX) was performed. This model was then used to train the neural PID tuner. A special MATLAB toolbox "SmatPID Toolbox" was developed to automate the process of controller synthesis. The resulting controller was tested in a laboratory coal-gas furnace control system to track specified air flow rates.
|Number of pages||6|
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 21 Nov 2019|
|Event||4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019 - Yalta, Crimea, Ukraine|
Duration: 15 Sep 2019 → 22 Sep 2019