First published 9/30/2026, 2:42:15 AM · Last updated 9/30/2026, 2:42:15 AM

Resilient Neural-Network-Based Model Reference Adaptive Sliding Mode Control of Uncertain Multimanipulator Systems With Multiple Faults

IEEE journal article published 2026-01-01 describing a resilient neural-network-based adaptive sliding mode control approach for uncertain multimanipulator systems experiencing multiple faults. The provided source metadata includes publisher and content type but no additional technical or impact details.

Categories: technology, science-and-space

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Confidence: 5/10How certain the assessment is based on the clarity and evidence in the cited reporting.
Geographic reach: 1/10How widely the event reaches, from a local area (1) to worldwide impact (10).
Global importance: 3/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 2/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 7/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 2/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

The article presents a technical control method for multimanipulator systems that may interest researchers and engineers in related fields.

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Resilient Neural-Network-Based Model Reference Adaptive Sliding Mode Control of Uncertain Multimanipulator Systems With Multiple Faults

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