Aerospace Instrumentation and Control Systems: Challenges, Innovations, and Future Prospects

Megha Kapoor

Megha Kapoor B.Tech Final Year Student, Department of Instrumentation and Control Engineering, Institute of Engineering and Technology (IET), Indore, India

Abstract

Aerospace systems rely heavily on sophisticated instrumentation and advanced control mechanisms to ensure precision, safety, and efficiency in extreme environments characterized by high altitudes, intense radiation, vast temperature variations, and unpredictable dynamics. As aerospace missions become increasingly complex—ranging from commercial aviation to interplanetary exploration—the demands on instrumentation accuracy, system autonomy, data management, and fault tolerance have intensified. This review discusses the current challenges faced in aerospace instrumentation and control, including environmental resilience, precision under dynamic conditions, secure communication, and real-time decision-making. It highlights recent innovations such as smart miniaturized sensors, AI-driven adaptive control systems, fiber optic sensor networks, and fault-tolerant architectures that are transforming the aerospace sector. Emerging trends like quantum sensing, autonomous spacecraft navigation, integrated structural health monitoring, and cybersecurity advancements are also explored. By synthesizing developments across sensor technologies, autonomous control, artificial intelligence (AI) integration, and cybersecurity, this article provides a comprehensive overview of the field. The review concludes by identifying critical opportunities for research and development that could shape the next generation of aerospace systems, emphasizing the importance of interdisciplinary collaboration to overcome existing barriers and propel aerospace engineering into a new era of innovation.

References

1. Bogue R. MEMS sensors: past, present and future. Sensor Review. 2007 Jan 30;27(1):7-13.
2. Bortoff SA. Path planning for UAVs. InProceedings of the 2000 american control conference. ACC (IEEE
Cat. No. 00CH36334) 2000 Jun 28 (Vol. 1, No. 6, pp. 364-368). IEEE.
3. Anderson K. Development of an Encrypted Wireless System for Body Sensor Network Applications.
4. Bekey GA, Robots A. From biological inspiration to implementation and control.
5. Sandhu RS. Role-based access control. InAdvances in computers 1998 Jan 1 (Vol. 46, pp. 237-286). Elsevier.
6. Smarsly K, Law KH. Decentralized fault detection and isolation in wireless structural health monitoring
systems using analytical redundancy. Advances in Engineering Software. 2014 Jul 1;73:1-0.
7. Vachtsevanos GJ, Lewis F, Roemer M, Hess A, Wu B. Intelligent fault diagnosis and prognosis for engineering
systems. Hoboken: Wiley; 2006 Sep 13.
8. Willsky AS. A survey of design methods for failure detection in dynamic systems. Automatica. 1976 Nov
1;12(6):601-11.
9. Abate A, Prandini M, Lygeros J, Sastry S. Probabilistic reachability and safety for controlled discrete time
stochastic hybrid systems. Automatica. 2008 Nov 1;44(11):2724-34.
10. Livne E. Future of airplane aeroelasticity. Journal of Aircraft. 2003 Nov;40(6):1066-92.
11. Rashvand HF, Abedi A, Alcaraz-Calero JM, Mitchell PD, Mukhopadhyay SC. Wireless sensor systems for space
and extreme environments: A review. IEEE Sensors Journal. 2014 Sep 19;14(11):3955-70.
12. Sutton RS, Barto AG. Reinforcement learning: An introduction. Cambridge: MIT press; 1998 Mar 1.
13. Ukwandu E, Ben-Farah MA, Hindy H, Bures M, Atkinson R, Tachtatzis C, Andonovic I, Bellekens X. Cyber-security challenges in aviation industry: A review of current and future trends. Information. 2022 Mar 10;13(3):146.
14. Xie Z, Wang Y, Lu C, Dai L. Sluggish hydrogen diffusion and hydrogen decreasing stacking fault energy in a
high-entropy alloy. Materials Today Communications. 2021 Mar 1;26:101902.
15. Fekih A. Fault diagnosis and fault tolerant control design for aerospace systems: A bibliographical review.
In2014 American Control Conference 2014 Jun 4 (pp. 1286-1291). IEEE.