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Machine Learning in Flight Control: Opportunities and the Certification Nightmare
Introduction: Power Meets Reality Machine Learning (ML) is no longer a lab curiosity in aerospace. It is already used for fault detection, sensor fusion, adaptive control assistance, and decision support. The promise is seductive: controllers that adapt, systems that anticipate failures, and aircraft that operate closer to optimal performance envelopes. But aviation is not…
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N-Version Programming and Design-Fault Tolerance in Safety-Critical Actuators
Safety-critical aerospace systems demand reliability far beyond ordinary software engineering standards. In modern fly-by-wire architectures, actuators that drive control surfaces — elevators, ailerons, rudders, flaps, and high-authority maneuvering systems — must function correctly under all circumstances. Hardware redundancy alone cannot guarantee this; design faults in software remain a major threat. This is where N-Version…