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<p>Satellite failure detection, isolation, and recovery (FDIR) is critical for mission autonomy, yet its implementation on resource-constrained nanosatellites presents significant challenges. This paper addresses these challenges by presenting a rigorous performance evaluation of a flexible, CLIPS-based FDIR system on a diverse suite of commercial and space-relevant microcontroller architectures, including ARM Cortex-R5F, M7, M4, M0+, and the SPARC V8 (LEON3). Our empirical findings establish the viability of this knowledge-based approach on modern, low-cost hardware, demonstrating that its practical application is governed by a clear set of performance trade-offs. The results reveal a wide performance spectrum, with rule execution times for nominal monitoring tasks ranging from approximately 60&#xa0;<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\upmu\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">μ</mi> </math></EquationSource> </InlineEquation>s on a high-performance ARM Cortex-M7 to over 4000&#xa0;<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\upmu\)</EquationSource> <EquationSource Format="MATHML"><math> <mi mathvariant="normal">μ</mi> </math></EquationSource> </InlineEquation>s on a simulated LEON3. We identify the data interface for fact creation and assertion as a primary performance bottleneck, often consuming more time than the core reasoning process. This research provides tangible data to guide satellite system architects in selecting appropriate hardware, confirming that expressive, rule-based FDIR is a feasible and resilient solution for the next generation of small spacecraft</p>

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Performance of rule-based system CLIPS on microcontrollers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月12日

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  • Sascha Wanninger

摘要

Satellite failure detection, isolation, and recovery (FDIR) is critical for mission autonomy, yet its implementation on resource-constrained nanosatellites presents significant challenges. This paper addresses these challenges by presenting a rigorous performance evaluation of a flexible, CLIPS-based FDIR system on a diverse suite of commercial and space-relevant microcontroller architectures, including ARM Cortex-R5F, M7, M4, M0+, and the SPARC V8 (LEON3). Our empirical findings establish the viability of this knowledge-based approach on modern, low-cost hardware, demonstrating that its practical application is governed by a clear set of performance trade-offs. The results reveal a wide performance spectrum, with rule execution times for nominal monitoring tasks ranging from approximately 60  \(\upmu\) μ s on a high-performance ARM Cortex-M7 to over 4000  \(\upmu\) μ s on a simulated LEON3. We identify the data interface for fact creation and assertion as a primary performance bottleneck, often consuming more time than the core reasoning process. This research provides tangible data to guide satellite system architects in selecting appropriate hardware, confirming that expressive, rule-based FDIR is a feasible and resilient solution for the next generation of small spacecraft