Artifficial Intelligence Driven Process Control Systems

Artificial Intelligence Driven Process Control Systems introduces students to the principles, methods, and practical challenges of controlling industrial and cyber-physical systems using both classical and artificial intelligence-based approaches. The course begins with the fundamentals of process control, feedback, sensors, system modelling, and PID regulation, and gradually extends these concepts toward adaptive control, fuzzy logic, machine learning, reinforcement learning, digital twins, and intelligent industrial automation.

The course emphasises the practical integration of AI into real control architectures rather than treating AI as a stand-alone technology. Students learn how data from sensors can be processed, interpreted, and used to support prediction, optimisation, fault detection, adaptive decision-making, and supervisory control. Special attention is given to implementation constraints, safety, explainability, lifecycle management, human oversight, and industrial deployment, preparing students to design and critically evaluate AI-driven control solutions for modern manufacturing, robotics, energy, and process-industry applications.