Internet of Things Based Digital Twin Model Construction and Online Fault-Tolerant Control of Hypersonic Flight Vehicle

Abstract

This paper proposes a novel framework for the online fault-tolerant control of hypersonic flight vehicles (HFV). The framework contains two steps. Firstly, based on the Internet of Things (IoT) and digital twin (DT) technology, a hypersonic flight vehicle digital twin (HFVDT) model is constructed. This HFVDT model can represent the real model and the parameter changes in HFV in real-time, and can update itself by the designed updating law through the flight data acquired by IoT. Then, the model changes caused by a fault can be fed back in real-time. Based on the real-time model, a model predictive static programming (MPSP) based controller design method is proposed to solve the online fault-tolerant control problem of HFV. MPSP provides a feasible online solution to optimal control problems with constraints. By converting the nonlinear optimal control problem to a static optimization the problem, the quantity of computation is greatly reduced, and then the optimal can be solved online. By the HFVDT and MPSP framework, the model change can be monitored and then an optimal controller can be constructed in real time. In this case, the fault-tolerant control problem of HFV can solved and the tracking performance is guaranteed. Finally, the novel framework is carried out on a numeral simulation to show its effectiveness.

Keywords

• hypersonic flight vehicles
• digital twin
• model predictive static programming
• fault-tolerant control