Introduction to Advanced Process Control

Industrial processes require precise, automated regulation to maintain safety, maximize efficiency, and ensure product quality. This course introduces you to the core principles of Advanced Process Control (APC), bridging the gap between classical feedback loops and modern industrial automation. By reading through this comprehensive, text-based course, you will transition from understanding simple single-loop controllers to conceptualizing the multi-variable control strategies used in modern chemical plants, refineries, and manufacturing facilities. What you'll learn: - Understand the fundamental terminology and limitations of classical PID control. - Explore system identification techniques to build mathematical models of physical processes. - Learn the basic principles of Model Predictive Control (MPC) and its industrial applications. - Study state estimation and filtering techniques to manage noisy sensor data. - Analyze multi-variable systems and strategies to handle loop interactions. - Examine how modern industrial data streams and internet of things (IIoT) architectures integrate with control systems. You will start by mastering foundational process dynamics and control terminology before moving step-by-step into linear systems, state-space representations, and optimization-based control strategies. The material is presented through clear written explanations, step-by-step mathematical breakdowns, and practical engineering scenarios. This course is designed for engineering students, junior process engineers, and automation technicians looking for a solid, accessible introduction to advanced control concepts without requiring an advanced mathematical background. Start reading today to build a strong foundation in modern industrial process control.