Robust fuzzy parallel distributed compensation PI control of non-linear plant
Snejana T. Yordanova, Bilyana Tabakova · International Conference on Artificial Intelligence · 2009
Parallel-distributed compensation (PDC) has proven to be a simple and efficient tool for building of process fuzzy logic controllers (FLCs) for non-linear plants with time delay and model uncertainty. This paper presents the design and the application of a PDC FLC for control of the liquid temperature in a tank via the average heat from electrical heater. First a Takagi-Sugeno (T-S) dynamic model of the non-linear plant is derived using experimental data, collected during the operation of the plant in various operating points under different disturbances. The fuzzy T-S model performs fuzzy blending of three high order inertial linear models, each approximated with Ziegler-Nichols first order time lag with time delay and describing the plant in a local linear sub-domain of operation. Next a PDC FLC is built of three incremental PI linear controllers in the consequents of the corresponding fuzzy rules, each compensating the local linear plant dynamics, and all ensuring a soft switching between control actions. Then the closed loop fuzzy system step response is simulated in MATLAB™. The settling time and the overshoot show that the PDC controller handles set point and disturbance changes better than a conventional PI controller.