H∞ Control-Based Robust CAS Design for QTW-UAV via the Multiple-Model Approach with Particle Swarm Optimization

Abstract

Quad-Tilt-Wing (QTW) Unmanned Aerial Vehicle (UAV) is one of the promising types of UAVs because of its high-speed cruise performance similar to fixed-wing aircraft and VTOL (Vertical TakeOff and Landing) ability like helicopters. The control performance of our previously designed Control Augmentation System (CAS) for the aircraft was not satisfactory due to the oscillatory motions in flight tests. This paper thus presents an H∞ control-based robust CAS design for QTW-UAV via multiple-model approach with Particle Swarm Optimization (PSO) to suppress the oscillatory motions. Although the adoption of the multiple-model approach to obtain robust CAS gains is the same as in our previous design, our new method has two unique features in contrast to the previously used method, that is, the design requirement for CAS gains is given in the frequency domain to shape the frequency responses from attitude command to attitude error and PSO is used to reduce the numerical complexity coming from a brute-force method, i.e., the gridding method. The overall control performance of the designed CAS gains is examined by human-in-the-loop nonlinear flight simulations. As an extension of the proposed method, we consider the situation in which uncertainty models with different probabilistic densities should be incorporated into the nominal model and show that the nominal performance can be improved at the expense of slight performance degradation for the models with small probabilistic density.