Intelligent approaches for linear controllers tuning with application to temperature control

Abstract

Despite the new sophisticated controllers the linear PI/PID controllers keep the leading position in industrial implementations due to their simplicity, easy and well developed design and tuning, good system performance and robustness and universal application area. Various enhancements have been suggested to enlarge their range of operation with good performance. Fuzzy logic (FL) and genetic algorithms (GAs) offer proper intelligent solutions for improving the PI/PID controllers auto-tuning and adaptation to successfully deal with plant nonlinearity, inertia and changing parameters without plant model. The aim of this research is to develop a simple for engineering use method for design of a fuzzy two-level controller (FTLC) of a linear PI/PID controller and a FL supervisor. The FL supervisor tunes on-line the scaling of the basic PI/PID controller's gains depending on performance indicators. The basic FTLC parameters are off-line optimized using GAs and a proposed fitness function of system performance and energy efficiency which is estimated in system simulation with a GA developed T-S plant model. The method is tested in real time control of the temperature in a laboratory – scale dryer. The result is decreased settling time, overshoot and energy consumption in the whole range of operation of the nonlinear plant.