Iterative Feedback Tuning of Model-Free Intelligent PID Controllers

Abstract

In the last decades, model-free control (MFC) has become an alternative for complex processes whose models are not available or are difficult to obtain. Among the model-free control techniques, intelligent PID (iPID) algorithms, which are based on the ultralocal model parameterized with the constant α and including a classical PID, are used in many applications. This paper presents a new method for tuning iPID controllers based on the iterative feedback tuning (IFT) technique. This model-free tuning technique iteratively optimizes the parameters of a fixed structure controller using data coming from the closed-loop system operation. First, the discrete transfer functions of the iPID are deduced, considering the first and second order derivatives of the output variable from the ultralocal model. Using the discrete transfer functions, the iPID controllers become the fixed structure type, and the IFT parameter tuning method can be applied. Thus, in addition to the classical gains of the PID algorithm, the value of the parameter α is also obtained, which is usually determined by trial-and-error. The performances of the IFT-tuned iPID controllers were experimentally tested and validated in real-time using Quanser AERO 2 laboratory equipment with a one degree of freedom (1-DOF) configuration.