Robust approximate optimal control for air‐breathing hypersonic vehicle

Abstract

This paper investigates the robust approximate optimal control problem for air-breathing hypersonic vehicle (AHV). By input-output linearzation and introducing auxiliary variables, the high-order nonlinear AHV dynamics are transformed to a second-order feedback decoupling model. Then a virtual command is designed by back-stepping strategy to guarantee the practical finite-time convergence of tracking error. In order to drive the AHV with uncertainties to follow the virtual command, a robust approximate optimal controller based on adaptive dynamic programming (ADP) is proposed. Different from the conventional robust method, both the robustness and the input cost are taken into consideration in the proposed controller, which can optimize the control actions and hence avoid the chattering. Besides, the proposed controller adopts a single critic network design instead of actor-critic structure, which ensures the stability of the system autonomously and simplifies the implementation procedure. The simulation results show the effectiveness of the proposed scheme.

On policy iteration‐based discounted optimal control

“…Besides, Yang et al 8 designed the fixed‐time dynamic event‐triggered optimal controller for systems with dead‐zone input nonlinearities based on ADP technique. More interesting works on ADP technique are refered to the works of Han et al, Wang et al and Zhang et al 9–11 …”

“…Besides, Yang et al 8 designed the fixed-time dynamic event-triggered optimal controller for systems with dead-zone input nonlinearities based on ADP technique. More interesting works on ADP technique are refered to the works of Han et al, Wang et al and Zhang et al [9][10][11] As is known to all, the objective of optimal control is to design an optimal control law that minimizes a predefined performance index. 12 There are various forms of performance indexes, such as the quadratic performance index, [13][14][15][16][17] the average performance index, 18,19 and the discounted performance index.…”