5. Identification of a Flexible Aircraft Derivatives

This chapter discusses the neural modeling of the flexible aircraft and how to extract the aerodynamic derivatives and structural mode shape parameters of flexible modes using the neural partial differentiation (NPD) method. The effects of flexibility on the flight dynamics of an aircraft have been shown to be quite significant, especially as the frequencies of its elastic modes become lower and approach those of the rigid body modes (Zerweckh et al. 1990; Meirovitch and Tuzcu 2001). The chapter discusses the neural modeling of the flexible aircraft and how to extract the aerodynamic derivatives and structural mode shape parameters of flexible modes using the NPD method. The effects of flexibility on the flight dynamics of an aircraft have been shown to be quite significant, especially as the frequencies of its elastic modes become lower and approach those of the rigid body modes (Colin et al. 2008; Majeed 2014). The characteristics of such flexible aircraft are altered significantly from those of a rigid aircraft, and the design of the flight control system may become drastically more complex (Bucharles and Vacher 2002). Therefore, mathematical modeling of a flexible aircraft for dynamic analysis and control system design is a major issue in flexible aircraft dynamics. The characteristics of such flexible aircraft are altered significantly from those of a rigid aircraft, and the design of the flight control system may become drastically more complex. Therefore, mathematical modeling of a flexible aircraft for dynamic analysis and control system design is a major issue in flexible aircraft dynamics.