The problem of the robust flight control is very actual in the last time, especially in the area of unmanned aerial vehicles (UAV). It is explained by the fact, that parameters of small UAV dynamic models are very vulnerable towards the changeable atmosphere conditions; therefore there is significant uncertainty of controlled plant's models as well as of the spectral properties of the exogenous disturbances. One of the effective ways to overcome these difficulties is the application of the fuzzy control principles. Fuzzy control became a good challenge to the classical control approaches, especially in the cases, when controlled plant and external disturbances possess uncertainty, time-varying dynamic characteristics, incomplete measurement of the state space vector components etc. However, the realization of fuzzy controller imposes the choice of many parameters by the designer, such as the shape of membership functions, inference strategy etc. This paper is devoted to the substantiation of this principle in general case via application of the sensitivity theory, which has to facilitate the choice of fuzzified part of the entire robust 'crisp' structure. This 'crisp' robust controller would be used as prototype for creation of the combined controller. In order to increase the zone of uncertain parameters of aircraft model with preserving the performance and robustness of control system, it is necessary to augment this system with the means of adaptation. That is why in this paper it is proposed the method of fuzzy controller adaptation via application of the fuzzy inverse model. The 'crisp' analog of this method is well-known method of reference model adaptive control, which realizes the searchless real-time adaptation of controller's parameters to the changing of plant's model during process of control. So the first of all it is necessary to consider briefly the procedure of the 'crisp' robust controller synthesis, which is used for determination of the dynamic feedback of the 'combined' controller and simultaneously for creation of the reference model for fuzzy controller tuning. In the paper adaptive robust autopilot with combined structure is considered. This structure uses the crisp' feedback with hard computing and fuzzy controller with soft computing, the structure of the crisp prototype of an autopilot is designed via robust H2/Hinfinity - optimization. The sensitivity theory is applied to justify, which part of control system to be fuzzified. The fuzzy controller designed has the ability of learning from the reference model in order to adjust its parameters. As case study, the longitudinal channel of a small UAV autopilot is considered to show the efficiency of the proposed method.
Hard and soft computing in the robust flight control systems
2007
10 Seiten, 4 Bilder, 11 Quellen
Aufsatz (Konferenz)
Englisch
Online Contents | 1996
|British Library Online Contents | 1996
|Nonlinear robust control for flight control systems
British Library Online Contents | 1998
|Robust Design in Flight Control Systems
British Library Online Contents | 1994
|Robust multivariable flight control
TIBKAT | 1994
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