Data-Based Suboptimal Tracking Control for Hypersonic Flight Vehicle Subject to Input Delay, Input Amplitude Constraint, and Input Rate Constraint

A suboptimal tracking controller is designed for hypersonic flight vehicle (HFV) subject to input delay, input amplitude constraint, and input rate constraint in this article. The input delay, input amplitude constraint, and input rate constraint are all caused by physical constraints of HFV, and are inevitable, so they must be considered in controller design. The model of input delay, input amplitude constraint and input rate constraint are first developed and then they are all transformed into inequality constraints. With considered the inequality constraints, precompensation method is utilized and then the tracking controller design problem for HFV with inequality constraints is transformed into controller design of unconstrained augmented system. The optimal controller for the unconstrained augmented system can be viewed as suboptimal controller for HFV. Then with considered the advantage of reinforcement learning (RL), an online policy-iteration (PI) algorithm for the optimal controller of the unconstrained augmented system is given. Furthermore, considering the uncertainty and unmodeled dynamics of HFV, neural networks (NN) are utilized and a data-based solution strategy of integral reinforcement learning (IRL) is presented for the unconstrained augmented system. Simulation results on the nonlinear model of HFV are given to reflect the effectiveness of the designed method.