Advancing Industrial Automation: Highlights from Recent Research

Industries today face several challenges due to rapidly evolving market demands, stringent environmental regulations, and the growing integration of renewable energy sources. Addressing these issues requires the adoption of innovative technologies that foster adaptability, operational efficiency, and resilience [1]. Within this context, key research areas include robust control strategies, advanced fault detection systems, dynamic optimization techniques, and the development of sophisticated real-time monitoring models. These advancements, often based on learning algorithms and real-time problem-solving approaches, hold significant promise for transforming industrial processes. This Special Issue, “Recent Advances in Process Control and Monitoring”, marks the 10th anniversary of Processes by showing a curated selection of contributions. These works highlight notable progress in robust control [2,3,4], fault detection [5,6,7], dynamic optimization [2,8], and the application of cutting-edge monitoring and detection models for real-time solutions [9,10,11].