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Unified Simulation Test Facility for Aerospace Vehicles

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Advances in Decision Sciences, Image Processing, Security and Computer Vision (ICETE 2019)

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Abstract

Aerospace vehicle carries On-Board Control & Guidance (OBCG) software (s/w) resident on On-Board Mission Computer (OBMC). This OBCG s/w is validated on various simulation test-beds for various mission critical errors. Non Real Time Simulation (NRTS) test-bed is used to validate the s/w for implementation, functionality and performance. Robustness of Controller design is validated through Monte-Carlo Simulation (MCS). Hardware-In-Loop-Simulation (HILS) test-bed is used to validate OBCG s/w for functionality & performance in the presence of Real Time (RT) issues like communication delays, system lag, scheduling, interfacing, execution times & Hardware subsystems problems. Here, in this publication, a new concept of ‘Unified Simulation Test Facility for Aerospace Vehicles (USTFASV)’ is brought out, which facilitates Model Driven On-board Controller S/w Development (MDOBCSD), Non Real Time Simulation, Monte-Carlo Simulation with Test Automation (MCSTA), Real Time Full Simulation and Real Time Hardware-In-Loop-Simulation. This Test Facility unifies all the simulations on single platform.

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References

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Acknowledgment

Authors are grateful to Dr. G. Sateesh Reddy, Chairman DRDO, Sri B.H.V.S.N. Murthy, Director RCI, G. Venkat Reddy, OS, Director, DNEC and Sri. Vijaya Sankar, Sc-‘G’ for their constant encouragement in carrying out this research work.

The authors are also thankful to Sri U. Raja Babu, Programme Director AD, Dr. Y. Srinivasa Rao, PD (FV-Exo) and Sri R. Venkatrami Reddy, DPD (AD-Missions) for their useful suggestions in related areas.

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Correspondence to K. Rama Rao or B. Mangu .

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Rama Rao, K., Mangu, B., Rama Prasanna, M. (2020). Unified Simulation Test Facility for Aerospace Vehicles. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-030-24318-0_52

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