To capture the airspeed-dependent dynamics of flexible aircraft, high-order aeroservoelastic systems can generally be expressed as linear parameter-varying (LPV) models. This paper presents a comprehensive model order reduction and control design process for grid-based LPV systems, and takes the flexible aircraft FLEXOP as an example for verification. The LPV model order reduction method is extended from projection-based linear time-invariant methods through construction of continuous transformations. The corresponding algorithm can be programmed to automatically perform the model order reduction for LPV systems and simultaneously ensure the state consistency between grid points and the continuity of state-space data interpolation. By applying this method, a 680th-order high-fidelity LPV model of the FLEXOP aircraft is reduced to a control-oriented model with only 19 states. Considering that the frequencies of rigid-body and flexible modes are close under certain parameter conditions, an integrated design approach for rigid-flexible coupling control is employed in this paper. Instead of separately designing a baseline rigid-body flight controller and a flutter suppression controller for each unstable flexible mode, a parameter-dependent dynamic output-feedback controller is designed. The resulting controller effectively expands the flutter-free flight envelope, ensuring rigid-body attitude and velocity tracking performance while stabilising the two originally unstable flutter modes.

In this paper, we propose a two-loop structure to transform and stabilize the kinematic model of a nonholonomic mobile robot with two independently driven wheels. This two-loop structure consists of input-output pseudolinearization and gain scheduling techniques. A comparison with previous methods is included. The main contribution of this paper is to apply a input-output pseudolinearization transformation method and to use an effective pole-assignment strategy for stabilizing a mobile robot with two independently driven wheels. The proposed method has demonstrated superiority over previous methods.