Trajectory tracking control based on improved particle swarm optimization

Since the tightly coupled, highly nonlinear and notoriously uncertain nature of hypersonic flight vehicle(HFV) dynamics, any state which does not meet the constraint may lead the system states to diverge. In this paper, differential flatness approach is applied to linearize the longitudinal model of HFV. According to the established trajectory, all the time-varying states and control inputs can be obtained by differential flatness approach, which is advantageous to protect states from exceeding the constraint before flight simulation. A state feedback controller is proposed. An improved particle swarm optimization algorithm is proposed to obtain the optimal parameters, which can ensure both convergence property of the system and large enough search space of parameters. A case study is presented to illustrate the effectiveness of the proposed methodology.