Predictive Functional Control based on Fuzzy Model: Comparison with linear predictive functional control and PID control

MARKO LEPETIC; IGOR SKRJANC; HÉCTOR G. CHIACCHIARINI; DRAGO MATKO

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

SPRINGER

Lugar: Amsterdam; Año: 2003 vol. 36 p. 467 - 480

0921-0296

The implementation of the fuzzy predictive functional control (FPFC) on the magnetic suspension system is presented in the paper. The magnetic suspension system was in our case the pilot plant for magnetic bearing and is an open-loop unstable process, therefore a lead compensator was used to stabilize it. The high quality control requirements were a-periodical step response and zero steady-state error. Adding the integrator to a feedback causes overshoot. The solution to the problem was cascade control with fuzzy predictive functional controller in the outer loop. To cope with the unknown model parameters and the nonlinear nature of the magnetic system, a fuzzy identification based on FNARX model was used. After successful validation the obtained fuzzy model was used for controller design. The FPFC is compared with a cascade linear predictive functional control (PFC) and PID control. The results we obtained with the FPFC are very promising and hardly comparable with conventional control techniques.