Abstract
This article studies the robust intelligent control for the longitudinal dynamics of flexible hypersonic flight vehicle with input dead zone. Considering the different time-scale characteristics among the system states, the singular perturbation decomposition is employed to transform the rigid-elastic coupling model into the slow dynamics and the fast dynamics. For the slow dynamics with unknown system nonlinearities, the robust neural control is constructed using the switching mechanism to achieve the coordination between robust design and neural learning. For the time-varying control gain caused by unknown dead-zone input, the stable control is presented with an adaptive estimation design. For the fast dynamics, the sliding mode control is constructed to make the elastic modes stable and convergent. The elevator deflection is obtained by combining the two control signals. The stability of the dynamics is analyzed through the Lyapunov approach and the system tracking errors are bounded. The simulation is conducted to demonstrate the effectiveness of the proposed approach.
| Original language | English |
|---|---|
| Pages (from-to) | 5926-5936 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Neural Networks and Learning Systems |
| Volume | 34 |
| Issue number | 9 |
| DOIs | |
| State | Published - 1 Sep 2023 |
Keywords
- Dead-zone input
- flexible dynamics
- hypersonic flight vehicle (HFV)
- neural networks (NNs)
- singular perturbation decomposition (SPD)
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