HYBRID INTELLIGENT CONTROL SCHEME FOR SET-POINT TRACKING OF A FLEXIBLE MANOEUVRING SYSTEM

Advances in control theory has provided a wide variety of artificial intelligence design techniques in addition to the more traditional PDD approaches which have been applied to control of flexible manoeuvring systems. Robust optimal control of flexible structures with active feedback techniques requires good models of the base structure, and knowledge of the uncertainties of these models. Such information may not be easy to acquire for certain systems. It has been known that fuzzy-logic-based modelling and control could serve as a powerful methodology for dealing with imprecision and nonlinearity efficiently. On the other hand, classical control laws are designed for linear systems and they provide a preferable cost/benefit ratio. However, the presence of nonlinear effects limits their performances. Hybridization of fuzzy logic techniques and classical PDD control schemes will exploit the beneficial features of both categories. This paper addresses the problem of input tracking control of a nonlinear flexible system namely a twin rotor multi-input multi-output (MEMO) system (TRMS) in hovering mode using hybrid control approaches in simulation and real time situations. An ANFIS model of the TRMS is used to represent its behaviour in the simulation environment. The obtained results in real-time prove the efficiency of the proposed scheme.