Unfortunately, control systems struggle to predict, identify, and mitigate unanticipated failures which can take key ship systems offline producing safety risks and substantially increasing sustainment expenses. This paper introduces an advanced hybrid control scheme that improves ship performance and reduces maintenance costs by leveraging modern artificial intelligence methods to predict, detect, and manage unexpected auxiliary system faults.
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