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Adaptive fuzzy control of smart structures-anfis

Stavroulakis Georgios, Salonikos Salonikidis, Tairidis Georgios, Papachristoudis Ioannis

Πλήρης Εγγραφή

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Περίληψη

Smart structures incorporate sensors and actuators, as well as control mechanisms that provide the smart (intelligent) behaviour. The control system is, therefore, an important part of the system. Linear feedback of linear systems can be studied by using classical methods of control. Nonlinearity in the system or in the controller makes the problem much more complicated. Fuzzy and hybrid neuro-fuzzy controllers can be used in this case.In previous investigations (Tairidis et al. 2007) a fuzzy controller has been proposed and tested numerically on a smart beam composed of piezoelectric sensors and actuators. Manual tuning of the fuzzy controller can not lead to optimal performance. Among others, the controller has worse performance in terms of velocities and accelerations, as it can be expected due to it’s nonlinear feedback, that would lead to fatigue problems in the involved components. Previous attempts of our group to alleviate this problem have been based on the automatic tunning of the controller by means of a genuine global optimizer, namely the particle swarm optimization (Marinaki et al. 2010). In this paper an adaptive fuzzy controller based on the well-known ANFIS system has been tested.

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