Design of Robust Fuzzy Logic Controllers for Complex Non-linear Processes with Time Delay

The progress of industrial applications of fuzzy logic controllers (FLCs) for high performance control of complex, non-linear, time-varying processes, sets demands for their design - to be laid on theoretical grounds, to be general and simple, to bind together system robustness, stability and performance in the design objective as a guarantee for practical feasibility. The aim of this investigation is to develop and implement PI-like FLCs for robust control of complex industrial plants with time delay. The suggested simple and objective FLC design and parameter tuning procedures are based on the derived in previous work robust stability and robust performance criteria as modification of Popov stability criterion for the case of a fuzzy control system accounting also for system robustness. The data required is a simple approximate nominal plant model and a plant uncertainty model, both estimated by experts. First, a Mamdani incremental or a position PI single input fuzzy controller (SI FC) is designed with a fuzzy unit (FU) - sector bounded static non-linearity, and a LTI dynamic part. Next, a two input incremental PI FLC is developed on the basis of the du-e projection of the FLC control curve. Further a Sugeno neural-fuzzy plant predictor is designed and embedded in the control system feedback in order to reduce the effect of the plant time delay. The design procedures are applied to various industrial plants. Results from simulation and real time control using MATLAB (TM) allow to assess control system performance and to compare it with the performance of systems with ordinary PI controller.