An Optimized Pressure-Based Method for Thrust Vectoring Angle Estimation
Nanxing Shi,
Yunsong Gu,
Tingting Wu,
Yuhang Zhou,
Yi Wang,
Shuai Deng
Affiliations
Nanxing Shi
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
Yunsong Gu
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
Tingting Wu
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
Yuhang Zhou
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
Yi Wang
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
Shuai Deng
Key Laboratory of Unsteady Aerodynamics and Flow Control, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Yudao Street 29, Nanjing 210016, China
This research developed a pressure-based thrust vectoring angle estimation method for fluidic thrust vectoring nozzles. This method can accurately estimate the real-time in-flight thrust vectoring angle using only wall pressure information on the inner surface of the nozzle. We proposed an algorithm to calculate the thrust vectoring angle from the wall pressure inside the nozzle. Non-dominated sorting genetic algorithm II was applied to find the optimal sensor arrays and reduce the wall pressure sensor quantity. Synchronous force and wall pressure measurement experiments were carried out to verify the accuracy and real-time response of the pressure-based thrust vectoring angle estimation method. The results showed that accurate estimation of the thrust vectoring angle can be achieved with a minimum of three pressure sensors. The pressure-based thrust vectoring angle estimation method proposed in this study has a good prospect for engineering applications; it is capable of accurate real-time in-flight monitoring of the thrust vectoring angle. This method is important and indispensable for the closed-loop feedback control and aircraft attitude control of fluidic thrust vectoring control technology.
