ABSTRACT
Modern chemical and energy processes face unprecedented challenges due to tight environmental regulations, volatile energy markets, and increasing integration with renewable resources. Advanced process optimization and control strategies play a key role in achieving efficient, reliable, and sustainable operations. This presentation highlights recent advances in data-driven optimization and predictive control tailored for complex process systems. By bridging physics-based modeling with modern data-driven methodologies, these strategies enable real-time decision-making, fault tolerance, and flexible energy management across scale.
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