PID self-tuning control using a fuzzy adaptive mechanism

Abstract

The authors present a novel proportional-integral-derivative (PID) self-tuning control using a fuzzy adaptive mechanism for regulating industrial processes. The essential idea is to parameterize a Ziegler-Nichols-like tuning formula by a single parameter alpha , then to use an online fuzzy inference mechanism to self-tune the parameter. A comparative simulation study on various processes, including processes with long dead-time and non-minimum-phase processes, shows that the performance of the scheme improves considerably, in terms of set-point and bad disturbance responses, over the PID controllers well-tuned using both the classical and the more recent refined Ziegler-Nichols formula.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>