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Received May 4, 2017; Accepted Nov 1, 2017
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Morphing aircrafts, as a broad range of air vehicles and vehicle components that can make shape transition with internal morphing devices, can adapt to multimission requirements [1]. As a result, they will be a substitution, covering the roles of several different aircrafts that can allow optimized flight over a large flight envelope instead of merely one flight condition. However, this property will certainly bring great difficulties to the traditional modeling and control methods. Due to the massive change of aerodynamic configuration during flight, the morphing aircraft cannot be considered under full geometry variation and it must take the morphing structures as well as multirigid body variations into consideration. Therefore, unlike most conventional aircrafts which are only concentrated on a fixed-structure and treat themselves as a single rigid body, the consideration of morphing demands a combination with several research areas such as aerodynamic modeling [2], multirigid body dynamics [3], and flight control based on a large range of reference points [4]. Obviously, it is important to incorporate a wide range performance into modeling and controller for the dynamical systems that describe morphing aircrafts. LPV synthesis techniques naturally fit into this characteristic. By selecting appropriate operating conditions of the original nonlinear model, the complex dynamics in morphing process can be represented by LPV dynamic models [5]. LPV systems, being the specific instance of linear time-varying (LTV) systems, are the representation that the entries of the state-space matrices continuously depend on a time-varying parameter vector that belongs to a bounded compact set [6, 7]. Using LPV techniques, the dynamics of the original nonlinear systems can be reduced to the linear equations. Meanwhile, the controller outputs will be continuously “scheduled” according to the system operating conditions. Comparing with the classical gain schedule techniques [8], LPV control can display prominent advantages as it can theoretically...





