Attitude control of variable swept-wing aircraft: A novel composite control strategy

被引:2
作者
Chen, Xiaoming [1 ]
Meng, Lisha [1 ]
Liu, Jiaji [1 ]
Shen, Danqing [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Nanjing 210016, Peoples R China
关键词
Variable swept-wing near space vehicle; Disturbance observer; Actuator composite nonlinearity; Adaptive switching sliding mode control; Reinforcement learning; Adaptive event-triggered mechanism; SPACE-VEHICLES; TRACKING CONTROL;
D O I
10.1016/j.ast.2025.110043
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
To address the complex issues of discontinuous disturbances, parameter uncertainties, actuator deadzone, and saturation nonlinearity in Variable Swept-Wing Near Space Vehicles (NSV), an attitude controller combining reinforcement learning and adaptive switching sliding mode control is proposed, along with an adaptive threshold event-triggered mechanism to reduce the actuator executing frequency. Firstly, the motion characteristics of the Variable Swept-Wing NSV across the full range of operating modes are modeled as a nonlinear switched system. Secondly, a nonlinear switched disturbance observer is employed to estimate the composite disturbances caused by discontinuous disturbances and parameter uncertainties. By introducing a deadzone right inverse function and designing an auxiliary system, the composite nonlinearity of the actuator are effectively addressed. An adaptive multi-modal switching sliding mode controller is then proposed based on the backstepping method to achieve basic control. Subsequently, considering the higher dimensionality of aerodynamic control surfaces and the increased complexity of aerodynamic characteristics in the subsonic mode, which imposes stricter control requirements, a reinforcement learning-based controller is designed. Leveraging the self-learning and optimization capabilities of reinforcement learning, which does not rely on an accurate model, the controller achieves end-to-end control of the horizontal canard. Finally, an event-triggered mechanism with an adaptively varying threshold is also developed. The multi-Lyapunov stability theory and the average dwell-time theory are employed to guarantee the stability of the closed-loop nonlinear switched system while excluding the undesired Zeno behavior. Simulations and comparative experiments demonstrate that the proposed method achieves superior tracking accuracy and control performance, while the adaptive threshold event-triggered mechanism effectively reduces data transmission.
引用
收藏
页数:30
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共 47 条
[21]   Sliding Mode Control Based on High-Order Linear Extended State Observer for Near Space Vehicle [J].
Li, Ouxun ;
Jiang, Ju ;
Deng, Li ;
Huang, Shutong .
INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, 2021, 2021
[22]   Adaptive sliding mode attitude control of two-wheeled robots for planetary auxiliary: From theory to applications ☆ [J].
Liu, Shuangxi ;
Lin, Zehuai ;
Huang, Wei ;
Yan, Binbin .
AEROSPACE SCIENCE AND TECHNOLOGY, 2024, 151
[23]   Reinforcement learning-based finite time control for the asymmetric underactuated tethered spacecraft with disturbances [J].
Lu, Yingbo ;
Wang, Xingyu ;
Liu, Ya ;
Huang, Panfeng .
ACTA ASTRONAUTICA, 2024, 220 :218-229
[24]   Deep Reinforcement Learning of UAV Tracking Control Under Wind Disturbances Environments [J].
Ma, Bodi ;
Liu, Zhenbao ;
Dang, Qingqing ;
Zhao, Wen ;
Wang, Jingyan ;
Cheng, Yao ;
Yuan, Zhirong .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
[25]   Disturbance-Observer-Based Adaptive Fuzzy Tracking Control for Unmanned Autonomous Helicopter With Flight Boundary Constraints [J].
Ma, Haoxiang ;
Chen, Mou ;
Feng, Gang ;
Wu, Qingxian .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2023, 31 (01) :184-198
[26]   Integrated attitude and landing control for quadruped robots in asteroid landing mission scenarios using reinforcement learning [J].
Qi, Ji ;
Gao, Haibo ;
Yu, Haitao ;
Huo, Mingying ;
Feng, Wenyu ;
Deng, Zongquan .
ACTA ASTRONAUTICA, 2023, 204 :599-610
[27]   Disturbance Observer-Based Prescribed-Time Tracking Control of Nonlinear Systems With Non-Vanishing Uncertainties [J].
Que, Ninan ;
Deng, Wenxiang ;
Zhou, Ning ;
Yao, Jianyong .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71 (06) :3131-3135
[28]   Robust Soft-Switching Multiple Model Predictive Control for Moving-Mass Reentry Vehicle [J].
Sun, Jiahui ;
Jing, Wuxing ;
Chen, Jie .
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2024, 47 (07) :1488-1498
[29]   Disturbance-observer-based control for non-homogeneous semi-Markov jump systems with time-varying delays [J].
Wang, Qian ;
Zhang, Xiaojun ;
Zhong, Shouming ;
Shi, Kaibo ;
Cheng, Jun ;
Katib, Iyad .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2024, 361 (01) :197-209
[30]   Direct thrust control for variable cycle engine based on fractional order PID-nonlinear model predictive control under off-nominal operation conditions [J].
Wang, Yangjing ;
Pan, Muxuan ;
Zhou, Wenxiang ;
Huang, Jinquan .
AEROSPACE SCIENCE AND TECHNOLOGY, 2023, 143