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Aerospace
Special Issues
Integrated Guidance and Control for Aerospace Vehicles
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Integrated Guidance and Control for Aerospace Vehicles

A special issue of Aerospace (ISSN 2226-4310).

Deadline for manuscript submissions: 31 May 2025 | Viewed by 2135

Special Issue Editors

Dr. Bin Zhao

E-Mail Website
Guest Editor
Institute of Precision Guidance and Control, Northwestern Polytechnical University, Xi’an 710072, China
Interests: aircraft design; aircraft guidance; attitude control; cooperative guidance; simulation and evaluation
Dr. Tuo Han

E-Mail Website
Guest Editor
School of Aeronautical Science and Engineering, Beihang University, 37, Xueyuan Road, Haidian District, Beijing 10019, China
Interests: constrained guidance and control; flight control; path planning
Dr. Pengyu Wang

E-Mail Website
Guest Editor
Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
Interests: constrained guidance and control; cooperative guidance; attitude control; intension identification
Dr. Wei Dong

E-Mail Website
Guest Editor
National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China
Interests: guidance and control of flight vehicles; cooperative control of multiagent systems; aerospace intelligent systems

Special Issue Information

Dear Colleagues,

Traditionally, the guidance and control systems of aerospace vehicles are designed independently, and their basic premise is based on the assumption of the spectrum separation principle. In recent decades, with the enhanced maneuverability and flight speed of aerospace vehicles, this assumption does not always make sense. In particular, the independent design becomes powerless under the fast dynamic performance and high precision requirements during high-speed flights with large maneuvers. To this end, the integrated guidance and control (IGC) design concept appeared and has attracted significant attention recently. The basic line of the IGC concept is to consider the relative motion and the dynamic characteristics as an integrated model governed by the guidance and control goals to be achieved. The IGC algorithm is capable of avoiding the delay between the inner and outer loops, simplifying the design cost, and improving the guidance and control performance from the perspective of all of the flight indicator requirements. Numerous techniques, including optimal control, sliding mode control, intelligent control, adaptive control, etc., have been employed to investigate the IGC system design problem. Although the recent progress in this field has witnessed various contributions, the design problem of IGC using various advanced control theories under multiple physical constraints or requirements remains open. To promote the development of aerospace technology, highlight the most recent advances, and provide a wide range of state-of-the-art trends in the IGC designs, as well as their applications, this Special Issue aims to collect the recent development of IGC design and share the latest results in relation to the theoretical and experimental investigations of the IGC concept for aerospace vehicles. It mainly invites articles from technical areas including but not limited to the new IGC design concept, modeling, analysis, and experimental verification.

Dr. Bin Zhao
Dr. Tuo Han
Dr. Pengyu Wang
Dr. Wei Dong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • integrated guidance and control
  • guidance and control modelling
  • constrained guidance and control
  • field-of-view limit
  • terminal impact constraint
  • actuator saturation
  • intelligent control

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Published Papers (3 papers)

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Research

24 pages, 1196 KiB  
Article
Integrated Guidance and Control for Strap-Down Flight Vehicle: A Deep Reinforcement Learning Approach
by Qinglong Zhang, Bin Zhao, Yifu Jiang, Jingyan Zhang and Jiale Zhang
Aerospace 2025, 12(5), 400; https://doi.org/10.3390/aerospace12050400 - 1 May 2025
Viewed by 181
Abstract
This paper proposes a three-dimensional (3D) deep reinforcement learning-based integrated guidance and control (DRLIGC) method, which is restricted by the narrow field-of-view (FOV) constraint of the strap-down seeker. By leveraging the data-driven nature of the deep reinforcement learning (DRL) algorithm, this method mitigates [...] Read more.
This paper proposes a three-dimensional (3D) deep reinforcement learning-based integrated guidance and control (DRLIGC) method, which is restricted by the narrow field-of-view (FOV) constraint of the strap-down seeker. By leveraging the data-driven nature of the deep reinforcement learning (DRL) algorithm, this method mitigates the challenges associated with integrated guidance and control (IGC) method design arising from model dependencies, thereby addressing the inherent complexity of the IGC model. Firstly, according to different states and actions, the pitch and yaw channels of the six-degree-of-freedom (6-DOF) IGC model are modeled as Markov decision processes (MDPs). Secondly, a channel-by-channel progressive training method based on the twin delayed deep deterministic policy gradient (TD3) algorithm is proposed. The agents of the pitch and yaw channels are trained using the TD3 algorithm independently, which substantially alleviates the complexity of the training process, while the roll channel is stabilized through the application of the back-stepping method. Thirdly, a comprehensive reward function is designed to simultaneously address the narrow FOV constraint and enhance the target engagement capability. Additionally, this function mitigates the issue of sparse rewards to some extent. Through Monte Carlo (MC) and comparative simulation verification, it is shown that the DRLIGC method proposed in this paper can effectively approach the target while maintaining the narrow FOV constraint and also has good robustness. Full article
(This article belongs to the Special Issue Integrated Guidance and Control for Aerospace Vehicles)
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24 pages, 1158 KiB  
Article
Koopman Predictor-Based Integrated Guidance and Control Under Multi-Force Compound Control System
by Qian Peng, Gang Chen, Jianguo Guo and Zongyi Guo
Aerospace 2025, 12(3), 213; https://doi.org/10.3390/aerospace12030213 - 6 Mar 2025
Viewed by 488
Abstract
This paper proposes a Koopman-predictor-based integrated guidance and control (IGC) law for the hypersonic target interceptor under the multi-force compound control. The strongly coupled and nonlinear guidance and control systems including the characteristics of the aerodynamic rudder, attitude control engine and orbit control [...] Read more.
This paper proposes a Koopman-predictor-based integrated guidance and control (IGC) law for the hypersonic target interceptor under the multi-force compound control. The strongly coupled and nonlinear guidance and control systems including the characteristics of the aerodynamic rudder, attitude control engine and orbit control engine are described as a linear IGC model based on the Koopman predictor. The proposed IGC law adapted to the linear IGC model is presented by combining the sliding mode control (SMC), the extended disturbance observer (EDO), and the adaptive weight-based control allocation scheme for being robust against the uncertainties and optimizing the fuel allocation for the fuel limited interceptor while intercepting the targets precisely. The stability of the proposed control law-based closed-loop system is guaranteed. The effectiveness and robustness of the proposed control law are proved by simulation comparisons and Monte Carlo tests. Full article
(This article belongs to the Special Issue Integrated Guidance and Control for Aerospace Vehicles)
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35 pages, 4185 KiB  
Article
Development and Evaluation of Transformer-Based Basic Fighter Maneuver Decision-Support Scheme for Piloting During Within-Visual-Range Air Combat
by Yiqun Dong, Shanshan He, Yunmei Zhao, Jianliang Ai and Can Wang
Aerospace 2025, 12(2), 73; https://doi.org/10.3390/aerospace12020073 - 21 Jan 2025
Viewed by 1006
Abstract
In within-visual-range (WVR) air combat, basic fighter maneuvers (BFMs) are widely used. Air combat engagement database (ACED) is a dedicated database for researching WVR air combat. Utilizing the data in ACED, a Transformer-based BFM decision support scheme is developed to enhance the pilot’s [...] Read more.
In within-visual-range (WVR) air combat, basic fighter maneuvers (BFMs) are widely used. Air combat engagement database (ACED) is a dedicated database for researching WVR air combat. Utilizing the data in ACED, a Transformer-based BFM decision support scheme is developed to enhance the pilot’s BFM decision making in WVR air combat. The proposed Transformer-based model significantly outperforms the baseline long short-term memory (LSTM)-based model in accuracy. To augment the interpretability of this approach, Shapley Additive Explanation (SHAP) analysis is employed, exhibiting the rationality of the Transformer-based model’s decisions. Furthermore, this study establishes a comprehensive framework for evaluating air combat performance, validated through the utilization of data from ACED. The application of the framework in WVR air combat experiments shows that the Transformer-based model increases the winning rate in combat from 30% to 70%, the average percentage of tactical advantage time from 4.81% to 14.73%, and the average situational advantage time share from 17.83% to 25.19%, which substantially improves air combat performance, thereby validating its effectiveness and applicability in WVR air combat scenarios. Full article
(This article belongs to the Special Issue Integrated Guidance and Control for Aerospace Vehicles)
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