Fine-tuning of multiloop PI controllers using fuzzy set theory

Abstract

This thesis proposes an intelligent way of fine-tuning multiloop PI controllers in multivariable distillation processes using linguistic fuzzy sets and fuzzy inference logic. This approach first requires reference dynamic curves which reflect the setpoint tracking and interaction rejection performance requirement by control engineer or operator. Linguistic fuzzy sets which describe the degrees of deviation from the reference dynamic curve patterns are then defined for each controlled output, and by minimizing the summation of the corrected membership values of controlled outputs we can get the proper PI parameters which improve the overall performance for transient and steady state behavior of closed-loop control system. Initial tuning parameters are set by the conventional multi-loop PI controller tuning methods such as BLT method which guarantees the stability of control system by mathematical frequency domain analysis. Simulation results for $2\times2,\; 3\times3,\; 4\times4$ distillation column cases illustrate improvement achieved by the proposed algorithm. For real implementation of this approach, a new WINDOWS based graphic user interface software ``FTUNER`` has been developed.