FUZZY SELF-TUNING OF PID CONTROLLERS

This paper presents a novel fuzzy self-tuning PID control scheme for r egulating industrial processes. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a single parame ter alpha, then to use an on-line fuzzy inference mechanism to self-tu ne the parameter. The fuzzy tuning mechanism, with process output erro r and error rate as its inputs, adjusts alpha in such a way that it sp eeds up the convergence of the process output to a set-point y(r), and slows down the divergence trend of the output from y(r). A comparativ e simulation study on various processes, including a second-order proc ess, processes with long dead-time and non-minimum phase processes, sh ows that the performance of the new scheme improves considerably, in t erms of set-point and load disturbance responses, over the PID control lers well-tuned using both the classical Ziegler-Nichols formula and t he more recent Refined Ziegler-Nichols formula.