Title :
Artificial intelligence in nonlinear process control based on fuzzy logic
Author :
Shteimberg, E. ; Kravits, M. ; Ellenbogen, A. ; Arad, M. ; Kadmon, Y.
Author_Institution :
Nucl. Res. Center-Negev (N.R.C.N), Beer-Sheva, Israel
Abstract :
Artificial Intelligence (AI) techniques are becoming useful as alternative approaches to conventional techniques or as components of integrated systems, coping with highly nonlinear processes. Fuzzy Logic (FL) is a major branch of AI based on human-like reasoning. In this paper a nonlinear system control design using a Hybrid of Fuzzy Logic and PI controller is presented. The proposed control scheme enables the controller to yield better control performance for highly nonlinear processes, compared to a regular PI controller.
Keywords :
PI control; fuzzy control; nonlinear control systems; process control; AI technique; FL controller; PI controller; artificial intelligence technique; fuzzy logic controller; human-like reasoning; integrated system; nonlinear process control; nonlinear system control design; Artificial intelligence; Fuzzy logic; Mathematical model; Nonlinear systems; Process control; Regulators; Uncertainty; AI; FUZZY LOGIC; IMC; PID;
Conference_Titel :
Electrical & Electronics Engineers in Israel (IEEEI), 2012 IEEE 27th Convention of
Conference_Location :
Eilat
Print_ISBN :
978-1-4673-4682-5
DOI :
10.1109/EEEI.2012.6376916
