Advanced Guidance and Control of Flight Vehicle: Theory and Application, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Dynamical Systems".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 883

Special Issue Editors


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Guest Editor
School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 510275, China
Interests: game theory; learning (artificial intelligence); missile guidance; optimal control; multi-agent systems
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Guest Editor
School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 510275, China
Interests: guidance and control; optimal control; trajectory planning; learning (artificial intelligence)
Special Issues, Collections and Topics in MDPI journals
School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
Interests: attitude control; satellite swarm dynamics and control; multi-objective optimization control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite you to submit the latest applied research in the application of guidance and control for missiles, hypersonic vehicles, and unmanned aerial vehicles to the Special Issue "Advanced Guidance and Control of Flight Vehicle: Theory and Application, 2nd Edition". The guidance and control technology of flight vehicles has always been a research hotspot in academia. In particular, how to provide more advanced and intelligent guidance and control technology for flight vehicles has become a research focus in recent years. This kind of problem involves a significant amount of mathematical theories and applications. Therefore, this Special Issue aims to conduct in-depth research on the mathematical theory and application of flight vehicle guidance and control. In this Special Issue, we welcome the submissions of scientific articles on advanced and effective guidance and control methods that solve the problems of trajectory optimization of flight vehicles, online planning and intelligent planning with high computational efficiency, advanced intermediate guidance theoretical methods, terminal guidance theoretical methods, intercept guidance and pursuit and escape guidance, nonlinear control, robust control, intelligent control of complex dynamics models, and so on. We encourage you to publish the latest research in the above fields and the results of simulation analysis and practical engineering applications in this Special Issue.

Prof. Dr. Haizhao Liang
Dr. Jianying Wang
Dr. Chuang Liu
Guest Editors

Manuscript Submission Information

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Published Papers (2 papers)

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Research

18 pages, 4855 KiB  
Article
A Reentry Trajectory Planning Algorithm via Pseudo-Spectral Convexification and Method of Multipliers
by Haizhao Liang, Yunhao Luo, Haohui Che, Jingxian Zhu and Jianying Wang
Mathematics 2024, 12(9), 1306; https://doi.org/10.3390/math12091306 - 25 Apr 2024
Viewed by 169
Abstract
The reentry trajectory planning problem of hypersonic vehicles is generally a continuous and nonconvex optimization problem, and it constitutes a critical challenge within the field of aerospace engineering. In this paper, an improved sequential convexification algorithm is proposed to solve it and achieve [...] Read more.
The reentry trajectory planning problem of hypersonic vehicles is generally a continuous and nonconvex optimization problem, and it constitutes a critical challenge within the field of aerospace engineering. In this paper, an improved sequential convexification algorithm is proposed to solve it and achieve online trajectory planning. In the proposed algorithm, the Chebyshev pseudo-spectral method with high-accuracy approximation performance is first employed to discretize the continuous dynamic equations. Subsequently, based on the multipliers and linearization methods, the original nonconvex trajectory planning problem is transformed into a series of relaxed convex subproblems in the form of an augmented Lagrange function. Then, the interior point method is utilized to iteratively solve the relaxed convex subproblem until the expected convergence precision is achieved. The convex-optimization-based and multipliers methods guarantee the promotion of fast convergence precision, making it suitable for online trajectory planning applications. Finally, numerical simulations are conducted to verify the performance of the proposed algorithm. The simulation results show that the algorithm possesses better convergence performance, and the solution time can reach the level of seconds, which is more than 97% less than nonlinear programming algorithms, such as the sequential quadratic programming algorithm. Full article
23 pages, 3790 KiB  
Article
Finite-Time Extended State Observer-Based Attitude Control for Hypersonic Vehicles with Angle-of-Attack Constraint
by Qingli Lu, Ruisheng Sun, Yu Lu and Xuanting Liu
Mathematics 2024, 12(7), 1061; https://doi.org/10.3390/math12071061 - 01 Apr 2024
Viewed by 415
Abstract
This paper develops and validates a modified backstepping control scheme for hypersonic vehicles (HSVs) with uncertain dynamics and angle-of-attack (AOA) constraint, which incorporates a novel finite-time extended state observer (FTESO) and a time-varying barrier Lyapunov function (BLF)-based controller. In order to ensure that [...] Read more.
This paper develops and validates a modified backstepping control scheme for hypersonic vehicles (HSVs) with uncertain dynamics and angle-of-attack (AOA) constraint, which incorporates a novel finite-time extended state observer (FTESO) and a time-varying barrier Lyapunov function (BLF)-based controller. In order to ensure that observation errors converge before the controller reaches the steady states, the “adding a power integrator” (AAPI) technique is utilized to design the FTESO by transforming the observation problem of the traditional extended state observer (ESO) into a stabilization problem. Combining time-varying constraints and tracking errors to construct the BLF, the backstepping control law that can adapt to large initial tracking errors is derived. Theoretical and comparative simulation results show that the proposed FTESO performs well in terms of speed and accuracy, and AOA is constrained within the prescribed region. Full article
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