Sensor and process noises reduction using a Luenberger state estimator with a stability augmentation system for a Hypersonic Transport Aircraft
This paper firstly, presents an autopilot strategy for a Hypersonic Transport Aircraft (HST) using a Stability Augmentation System (SAS) with a Luenberger estimator. The SAS is designed using Linear Quadratic Regulator (LQR) theory which, for HST, benefits the guaranteed robust dynamic stability pro...
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| Format: | Article |
| Published: |
The Research Publication
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/103173/ https://armejournal.org/index.php/arme/article/view/3346 |
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| Summary: | This paper firstly, presents an autopilot strategy for a Hypersonic Transport Aircraft (HST) using a Stability Augmentation System (SAS) with a Luenberger estimator. The SAS is designed using Linear Quadratic Regulator (LQR) theory which, for HST, benefits the guaranteed robust dynamic stability provided three theoretical requirements are met. The Luenberger estimator is incorporated into the autopilot design to estimate the state variables of the aircraft for the SAS. In the dynamic response simulation, sensor and process noises are inserted into the mathematical model. However, to date, knowledge of the sensor and process noises at the speeds and heights where the aircraft will be flying is limited. The simulation shows that the Luenberger estimator significantly filters the noise. This is an advantage for the HST as prior knowledge of the noises is not necessary when designing the Luenberger estimator. |
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