Research

24 pages, 3737 KiB

Open AccessArticle

Finite-Time Anti-Saturated Formation Tracking Control of Multiple Unmanned Aerial Vehicles: A Performance Tuning Way

by Taoyi Chen, Yaolin Lei, Huixiang Peng, Yanqiao Chen, Xinghua Chai and Zeyong Zhang

Mathematics 2023, 11(20), 4255; https://doi.org/10.3390/math11204255 - 11 Oct 2023

Viewed by 547

A highly effective control method is very important to guarantee the safety of the formation of flying missions for multiple unmanned aerial vehicles (UAVs), especially in the presence of complex flying environments and actuator constraints. In this regard, this paper investigates the formation [...] Read more.

A highly effective control method is very important to guarantee the safety of the formation of flying missions for multiple unmanned aerial vehicles (UAVs), especially in the presence of complex flying environments and actuator constraints. In this regard, this paper investigates the formation tracking control problem of multiple UAVs in the presence of actuator saturation. Firstly, a brand-novel finite-time anti-saturated control scheme is proposed for multiple UAVs to track the desired position commands, wherein the tracking performance is tuned by introducing a logarithmic function-based state-mapping policy. Then, an adaptive scheme based on projection rules is devised to compensate for the negative effects brought by the actuator saturation. Based on the proposed formation tracking controller, the finite-time formation tracking performance tuning and control saturation problems can be addressed simultaneously with a comparatively allowable system robustness. Finally, three groups of illustrative examples are organized to verify the effectiveness of the proposed formation tracking control scheme. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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14 pages, 3778 KiB

Open AccessArticle

Finite-Time Super Twisting Disturbance Observer-Based Backstepping Control for Body-Flap Hypersonic Vehicle

by Daiming Liu, Changwan Min, Jiashan Cui, Fei Li, Dongzhu Feng and Pei Dai

Mathematics 2023, 11(11), 2460; https://doi.org/10.3390/math11112460 - 26 May 2023

Viewed by 797

Abstract

This paper investigates the attitude control problem for underactuated body-flap hypersonic vehicles (BFHSVs) with mixed disturbances. First, the control-oriented model for BFHSV is introduced. Then, an improved finite-time super twisting disturbance observer (STDO) is designed. Finite-time convergence of estimate error and smoother inputs [...] Read more.

This paper investigates the attitude control problem for underactuated body-flap hypersonic vehicles (BFHSVs) with mixed disturbances. First, the control-oriented model for BFHSV is introduced. Then, an improved finite-time super twisting disturbance observer (STDO) is designed. Finite-time convergence of estimate error and smoother inputs are achieved. Meanwhile, a parametric command method is introduced to calculate the differential of inputs which can enhance the dynamic response of the closed-loop system. Subsequently, the virtual control signal is derived by a second-order filter to avoid the differential explosion problem. The overall stability of the closed-loop system is demonstrated by applying the Lyapunov stability theory. Finally, the performance of the proposed control scheme is evaluated through extensive and comparative numerical simulations under multiple disturbances. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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25 pages, 5085 KiB

Open AccessArticle

On-Orbit Verification of RL-Based APC Calibrations for Micrometre Level Microwave Ranging System

by Xiaoliang Wang, Xuan Liu, Yun Xiao, Yue Mao, Nan Wang, Wei Wang, Shufan Wu, Xiaoyong Song, Dengfeng Wang, Xingwang Zhong, Zhu Zhu, Klaus Schilling and Christopher Damaren

Mathematics 2023, 11(4), 942; https://doi.org/10.3390/math11040942 - 13 Feb 2023

Viewed by 1106

Abstract

Micrometre level ranging accuracy between satellites on-orbit relies on the high-precision calibration of the antenna phase center (APC), which is accomplished through properly designed calibration maneuvers batch estimation algorithms currently. However, the unmodeled perturbations of the space dynamic and sensor-induced uncertainty complicated the [...] Read more.

Micrometre level ranging accuracy between satellites on-orbit relies on the high-precision calibration of the antenna phase center (APC), which is accomplished through properly designed calibration maneuvers batch estimation algorithms currently. However, the unmodeled perturbations of the space dynamic and sensor-induced uncertainty complicated the situation in reality; ranging accuracy especially deteriorated outside the antenna main-lobe when maneuvers performed. This paper proposes an on-orbit APC calibration method that uses a reinforcement learning (RL) process, aiming to provide the high accuracy ranging datum for onboard instruments with micrometre level. The RL process used here is an improved Temporal Difference advantage actor critic algorithm (TDAAC), which mainly focuses on two neural networks (NN) for critic and actor function. The output of the TDAAC algorithm will autonomously balance the APC calibration maneuvers amplitude and APC-observed sensitivity with an object of maximal APC estimation accuracy. The RL-based APC calibration method proposed here is fully tested in software and on-ground experiments, with an APC calibration accuracy of less than 2 mrad, and the on-orbit maneuver data from 11–12 April 2022, which achieved 1–1.5 mrad calibration accuracy after RL training. The proposed RL-based APC algorithm may extend to prove mass calibration scenes with actions feedback to attitude determination and control system (ADCS), showing flexibility of spacecraft payload applications in the future. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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22 pages, 10612 KiB

Open AccessArticle

Fixed-Point Control of Airships Based on a Characteristic Model: A Data-Driven Approach

by Yanlin Chen, Shaoping Shen, Zikun Hu and Long Huang

Mathematics 2023, 11(2), 310; https://doi.org/10.3390/math11020310 - 06 Jan 2023

Viewed by 1691

Abstract

Factors such as changes in the external atmospheric environment, volatility in the external radiation, convective heat transfer, and radiation between the internal surfaces of the airship skin will cause a series of changes in the motion model of an airship. The adaptive control [...] Read more.

Factors such as changes in the external atmospheric environment, volatility in the external radiation, convective heat transfer, and radiation between the internal surfaces of the airship skin will cause a series of changes in the motion model of an airship. The adaptive control method of the characteristic model is proposed to extract the relationship between input and output in the original system, without relying on an accurate dynamic model, and solves the problem of inaccurate modeling. This paper analyzes the variables needed for two-dimensional path tracking and combines the guidance theory and the method of wind field state conversion to determine specific control targets. Through the research results, under the interference of wind, the PD control method and the reinforcement learning-based method are compared with a characteristic model control method. The response speed of the characteristic model control method surpasses the PD control method, and it reaches a steady state earlier than the PD control method does. The overshoot of the characteristic model control method is smaller than that of the PD control method. Using the control method of the characteristic model, the process of an airship flying to a target point will be more stable under the influence of an external environment. The modeling of the characteristic model adaptive control method does not rely on a precise model of the system, and it automatically adjusts when the parameters change to maintain a consistent performance in the system, thus reflecting the robustness and adaptability of the characteristic model adaptive control method in contrast with reinforcement learning. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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28 pages, 2789 KiB

Open AccessArticle

Intention Prediction of a Hypersonic Glide Vehicle Using a Satellite Constellation Based on Deep Learning

by Yu Cheng, Cheng Wei, Yongshang Wei, Bindi You and Yang Zhao

Mathematics 2022, 10(20), 3754; https://doi.org/10.3390/math10203754 - 12 Oct 2022

Cited by 2 | Viewed by 1430

Abstract

Tracking of hypersonic glide vehicles (HGVs) by a constellation tracking and observation system is an important part of the space-based early warning system. The uncertainty in the maneuver intentions of HGVs has a non-negligible impact on the tracking and observation process. The cooperative [...] Read more.

Tracking of hypersonic glide vehicles (HGVs) by a constellation tracking and observation system is an important part of the space-based early warning system. The uncertainty in the maneuver intentions of HGVs has a non-negligible impact on the tracking and observation process. The cooperative scheduling of multiple satellites in an environment of uncertainty in the maneuver intentions of HGVs is the main problem researched in this paper. For this problem, a satellite constellation tracking decision method that considers the HGVs’ maneuver intentions is proposed. This method is based on building an HGV maneuver intention model, developing a maneuver intention recognition and prediction algorithm, and designing a sensor-switching strategy to improve the local consensus-based bundle algorithm (LCBBA). Firstly, a recognizable maneuver intention model that can describe the maneuver types and directions of the HGVs in both the longitudinal and lateral directions was designed. Secondly, a maneuver intention recognition and prediction algorithm based on parallel, stacked long short-term memory neural networks (PSLSTM) was developed to obtain maneuver directions of the HGV. On the basis of that, a satellite constellation tracking decision method (referred to as SS-LCBBA in the following) considering the HGVs’ maneuver intentions was designed. Finally, the maneuver intention prediction capability of the PSLSTM network and two currently popular network structures: the multilayer LSTM (M-LSTM) and the dual-channel and bidirectional neural network (DCBNN) were tested for comparison. The simulation results show that the PSLSTM can recognize and predict the maneuver directions of HGVs with high accuracy. In the simulation of a satellite constellation tracking HGVs, the SS-LCBBA improved the cumulative tracking score compared to the LCBBA, the blackboard algorithm (BM), and the variable-center contract network algorithm (ICNP). Thus, it is concluded that SS-LCBBA has better adaptability to environments with uncertain intentions in solving multi-satellite collaborative scheduling problems. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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30 pages, 9901 KiB

Open AccessArticle

Attitude Control Method of Unmanned Helicopter Based on Asymmetric Tracking Differentiator and Fal-Extended State Observer

by Chen Cheng, Zian Wang, Chengxi Zhang and Yang Yang

Mathematics 2022, 10(19), 3439; https://doi.org/10.3390/math10193439 - 21 Sep 2022

Cited by 1 | Viewed by 1558

Abstract

In order to meet the constraints of velocity and acceleration of displacement and attitude motion of an unmanned helicopter during an automatic carrier landing mission, an asymmetric tracking differentiator, which could set the speed and acceleration limits in two directions of tracked signal [...] Read more.

In order to meet the constraints of velocity and acceleration of displacement and attitude motion of an unmanned helicopter during an automatic carrier landing mission, an asymmetric tracking differentiator, which could set the speed and acceleration limits in two directions of tracked signal motion respectively, was derived based on the tracking differentiator in the active disturbance rejection control method. Based on the proposed asymmetric tracking differentiator, a fal-extended state observer based on the fal function was added to construct the attitude and angular velocity controller which is programmable during the transition process of unmanned helicopters. The mathematical simulation and result analysis show that the newly proposed attitude estimation algorithm effectively compensates for the deficiencies of the existing methods, improves the anti-jamming capability and the accuracy of attitude estimation in the maneuvering process, achieving the expected design purposes. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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22 pages, 11533 KiB

Open AccessArticle

A Linear-Active-Disturbance-Rejection-Based Vertical Takeoff and Acceleration Strategy with Simplified Vehicle Operations for Electric Vertical Takeoff and Landing Vehicles

by Shengchen Mao, Zheng Gong, Zheng Ye, Zian Wang, Tongqing Guo and Chengxi Zhang

Mathematics 2022, 10(18), 3333; https://doi.org/10.3390/math10183333 - 14 Sep 2022

Cited by 3 | Viewed by 1422

Abstract

A practical vertical takeoff and acceleration strategy is developed for manned electric vertical takeoff and landing vehicles, with a simple vehicle operation principle defined. Firstly, a 6-DOF model is established for 120 kg reduced-scale protype electric vertical takeoff and landing vehicles, with its [...] Read more.

A practical vertical takeoff and acceleration strategy is developed for manned electric vertical takeoff and landing vehicles, with a simple vehicle operation principle defined. Firstly, a 6-DOF model is established for 120 kg reduced-scale protype electric vertical takeoff and landing vehicles, with its physical control principles illustrated. Then, a simple vehicle operation method is defined for the vehicle, where the conventional operation method for fixed-wings and helicopters is considered for a friendly stick response definition for pilots with different backgrounds. The defined simple vehicle operation principles are realized by a control architecture with a linear-active-disturbance-rejection-control-based inner loop stability augmentation system and an airspeed-based mode selection outer loop. This system is then used to perform a four-stage vertical takeoff and acceleration strategy, which targets at a smooth and safe transition. The Monte Carlo simulation results and the strategy simulations prove that the proposed strategy, which achieves the design target perfectly, can be easily performed with the developed simple vehicle operation system, and that it has sufficient robustness performance to reject at least 20% of the model’s uncertainties. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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22 pages, 4206 KiB

Open AccessArticle

Finite-Time Extended State Observer-Based Fixed-Time Attitude Control for Hypersonic Vehicles

by Jiaqi Zhao, Dongzhu Feng, Jiashan Cui and Xin Wang

Mathematics 2022, 10(17), 3162; https://doi.org/10.3390/math10173162 - 02 Sep 2022

Cited by 8 | Viewed by 1678

Abstract

A finite-time extended, state-observer-based, fixed-time backstepping control algorithm was designed for hypersonic flight vehicles. To enhance the robustness of the controller, two novel finite-time extended state observers were introduced to compensate for the negative effects of lumped disturbances such as uncertainties and external [...] Read more.

A finite-time extended, state-observer-based, fixed-time backstepping control algorithm was designed for hypersonic flight vehicles. To enhance the robustness of the controller, two novel finite-time extended state observers were introduced to compensate for the negative effects of lumped disturbances such as uncertainties and external disturbances. Two hyperbolic sine tracking differentiators were used to approximate the derivatives of the virtual control signals and guidance commands, thereby alleviating the computational burden associated with traditional backstepping control. Furthermore, a fixed-time backstepping attitude controller was used to guarantee that the tracking errors converged to a small neighbor of the origin in fixed time. According to the simulation results, the proposed controller outperformed a fixed-time sliding mode disturbance, observer-based, finite-time backstepping controller in terms of the tracking precision and convergence rate. Moreover, the proposed controller was noted to be robust in simulations involving lumped disturbances. Full article

(This article belongs to the Special Issue Applications of Machine Learning in Spacecraft and Aerospace Systems)

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