Numerical Process Control with MATLAB: Calculating Jacobian Matrices

In chemical process control, modeling real-world systems requires managing complex, nonlinear algebraic equations. To analyze and control these systems, engineers must linearize these equations using Jacobian matrices. This course provides a clear, step-by-step written guide to understanding and calculating Jacobian matrices numerically using MATLAB. You will transition from grasping the fundamental math behind multivariable linearization to writing clean, reusable MATLAB functions. By exploring numerical approximation techniques, you will gain the skills to analyze process stability and design robust control systems without relying on tedious analytical derivations. What you'll learn: - Understand the foundational role of Jacobian matrices in process control and linearization. - Apply the central differencing scheme to approximate partial derivatives numerically. - Write robust MATLAB functions to automate Jacobian calculations for nonlinear systems. - Analyze chemical engineering process models for stability and control design. - Implement modern MATLAB coding standards, including proper vectorization and type hinting. - Debug numerical approximation errors to ensure simulation accuracy. The course begins with essential mathematical definitions and core chemical engineering concepts, then moves step-by-step through numerical approximation algorithms, and concludes with practical MATLAB implementation exercises. It is designed for engineering students and practicing professionals who are new to numerical process control and want a solid, practical foundation. No advanced programming experience is required. Start mastering numerical linearization for process control today.