Article Highlight | 27-Oct-2025

Review on guidance and control of aerospace vehicles: recent progress and prospect

Shanghai Jiao Tong University Journal Center

The relationship between elastic deformation and elastic vibration on dynamics

image: 

  1. This schematic illustrates the intricate interconnections between different physical domains in aerospace vehicle guidance and control systems, demonstrating how thermal, structural, and aerodynamic effects interact throughout the vehicle's operation.
  2. The diagram reveals a sophisticated control system where real-time flight status data feeds into guidance & control laws, generating precise commands such as rudder deflection to maintain optimal trajectory and stability while accounting for varying flight conditions.
  3. The system must withstand extreme operational challenges, including intense aerodynamic heat during high-speed flight and fundamental structural strength limitations, while accounting for substantial airframe deformation and air-rudder deformation caused by combined thermal and mechanical loads.
  4. These interconnected factors create complex feedback loops that continuously modify the vehicle's aerodynamic properties and control effectiveness, necessitating advanced control approaches that simultaneously address coupled thermal, structural, and aerodynamic effects across the entire flight envelope.
view more 

Credit: Zian Wang, Pengcheng Cai, Zheng Gong, Chengxi Zhang, Shunyi Zhao, Jin Wu, Peng Dong.

As the global race for hypersonic and reusable space access intensifies, the demand for highly reliable and adaptive guidance and control (G&C) systems has never been greater. A comprehensive review published in Aerospace Systems now maps out the technological evolution and future trends in this critical field, synthesizing recent advances for next-generation aerospace vehicles.

Why Advanced G&C Systems Are Critical

Wide-Speed Domain Challenges: These vehicles operate across vastly different environments—from dense atmosphere to near-space—requiring control systems that can adapt to dramatic changes in aerodynamics, propulsion, and stability. Strong model uncertainties and the tight coupling between airframe, engine, and lightweight flexible structures further complicate controller design.

Multi-Phase Mission Complexity: Each distinct flight phase—ascent, orbit-entry, re-entry, terminal area energy management (TAEM), and landing—demands specialized guidance strategies and robust control under stringent path and process constraints like heat flux, dynamic pressure, and overload.

Key Advances in Control Methods

From PID to Intelligent Control: While PID control with gain scheduling remains widely used for its simplicity, methods like Sliding Mode Control (SMC), Adaptive Control, and Active Disturbance Rejection Control (ADRC) are gaining prominence for their superior robustness in handling strong nonlinearities and uncertainties.

Integrated Vehicle-Engine Control: New strategies are essential to address the tight coupling between airframe dynamics and the performance of combined-cycle engines, especially during critical mode transitions.

Managing Elasticity and Stability: As vehicles become lighter and more flexible, control systems must account for structural vibrations and "relaxed static stability" designs without sacrificing performance.

Guidance Breakthroughs Across Flight Phases

Ascent & Orbit-Entry: For the challenging ascent phase of combined-cycle vehicles, nominal trajectory tracking is common. For orbit-entry, Iterative Guidance Mode (IGM) enables high-precision orbital insertion. Online trajectory planning methods based on convex optimization show great promise for adaptability under contingencies like engine failure.

Re-Entry Guidance: This phase is particularly demanding due to complex constraints and uncertainties. While reference trajectory tracking is a baseline, Predictive-Correction guidance offers greater autonomy and robustness. Emerging intelligent guidance methods using neural networks allow for real-time trajectory reshaping to satisfy no-fly zones, heat constraints, and precise landing requirements.

TAEM & Autonomous Landing: The unpowered return and landing of reusable vehicles require precise energy management and handling of non-minimum phase dynamics. Advanced tracking guidance and deep learning-based controllers are being developed to achieve safe and accurate autonomous landings.

Future Outlook: The Path to Intelligent Autonomy

The review identifies machine learning, deep neural networks, and fully autonomous guidance as key enablers for the next generation of aerospace systems. These technologies are poised to revolutionize real-time trajectory optimization, fault tolerance, and decision-making—critical for both military and commercial applications such as global strike, satellite deployment, and future point-to-point transportation.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.