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Model-free fuzzy control of twin rotor aerodynamic systems

This paper suggests data-driven Model-Free Control (MFC) algorithms based on the combination of Takagi-Sugeno fuzzy (TSF) and intelligent proportional-integral (iPI) controllers. The new MFC algorithms are referred to as mixed TSF-iPI controllers, which are designed to control Single Input-Single Output (SISO) control structures for azimuth and pitch position control of a nonlinear twin rotor aerodynamic system (TRAS). The mixed TSF-iPI controllers are designed by fuzzifying the proportional-derivative term in the iPI controller structure. The performance of the SISO control structures with mixed TSF-iPI controllers and iPI controllers is compared by means of real-time experiments conducted on a TRAS laboratory equipment using controllers tuned in terms of a metaheuristic Gravitational Search Algorithm optimizer.