AI - Driven - Closed-Loop Control : A Recipe for Factory of the Future

AI-Driven Closed-Loop Control presents a modern approach to building intelligent, self-adapting factories by combining classical control principles with artificial intelligence and digital twins.Traditional automation systems rely on fixed logic and predefined rules. This book shows how AI transforms closed-loop control into a continuously learning system—one that senses real-world conditions, predicts outcomes, makes decisions, and automatically adjusts operations in real time.The book introduces a three-layer digital twin architecture that enables true closed-loop autonomy:Asset & Process Twin for real-time machine control and stabilityOperational & System Twin for production flow, quality, and energy optimizationIntelligence & Decision Twin where AI models analyze data, simulate outcomes, and guide control actionsBy connecting these digital twins through feedback loops, AI becomes an active participant in control—not just analytics. The result is a factory that can self-optimize, self-correct, and continuously improve across quality, productivity, maintenance, and sustainability.This book explains:How AI enhances classical closed-loop control systemsHow digital twins act as the bridge between physical and virtual factoriesHow feedback loops enable predictive, adaptive, and autonomous behaviorHow human operators collaborate with AI in decision-guided controlHow factories transition from automation to autonomyWritten for engineers, system architects, manufacturing leaders, and advanced students, AI-Driven Closed-Loop Control provides a practical and system-level perspective on designing the Factory of the Future—intelligent, resilient, and data-driven. Read more