Process Control Course

Lesson 1 • Process Control Objectives and Metrics

Defines performance criteria such as stability, setpoint tracking, and disturbance rejection. Frames metrics used to evaluate controllers later in the course.

Lesson 2 • Process Variables and Signals

Identifies the variables manipulated and measured in a control loop. Links variable types to control strategy selection.

Lesson 3 • Introduction to Process Control

Defines process control and its role in industrial operations. Establishes vocabulary used throughout the course.

Lesson 4 • Process Dynamics Fundamentals

Explains how processes respond to input changes over time. Provides the dynamic understanding needed for controller design.

Lesson 1 • Simulation of Process Models

Implements process models in simulation environments to predict dynamic responses. Supports hands-on validation before physical implementation.

Lesson 2 • Transfer Function Representation

Converts differential equations into Laplace-domain transfer functions. Enables frequency-domain analysis used in later controller design chapters.

Lesson 3 • First-Principles Modelling

Applies mass and energy balances to derive dynamic process models. Provides the analytical foundation for understanding process behaviour.

Lesson 4 • Model Validation and Uncertainty

Assesses model accuracy against measured plant data and quantifies uncertainty. Prepares students to select robust control designs.

Lesson 1 • Stability Concepts and Criteria

Defines BIBO and Lyapunov stability and introduces the Routh-Hurwitz criterion. Provides the theoretical basis for all subsequent stability analysis.

Lesson 2 • Nyquist Criterion and Stability

Applies the Nyquist stability criterion to systems with time delays and right-half-plane poles. Extends stability analysis beyond Bode plot limitations.

Lesson 3 • Bode Plot Analysis

Constructs and interprets Bode magnitude and phase plots for open-loop systems. Enables gain and phase margin calculation for stability assessment.

Lesson 4 • Robustness and Sensitivity Functions

Evaluates sensitivity and complementary sensitivity functions to quantify robustness. Links frequency-domain metrics to real-world disturbance and noise rejection.

Lesson 1 • Performance-Based Tuning

Optimises PID parameters using integral error criteria and simulation-based search. Connects tuning decisions to quantified performance outcomes.

Lesson 2 • Classical Tuning Methods

Applies Ziegler-Nichols, Cohen-Coon, and IMC-based tuning rules to set PID parameters. Provides practical starting points for controller commissioning.

Lesson 3 • PID Controller Modes

Explains proportional, integral, and derivative actions and their individual effects. Enables students to select appropriate control modes for a given process.

Lesson 4 • Feedback Control Loop Structure

Analyses the closed-loop architecture and the role of each loop element. Establishes the framework for PID controller analysis.

Lesson 1 • PLC and DCS Control Platforms

Surveys programmable logic controller and distributed control system architectures. Connects hardware capabilities to control algorithm deployment.

Lesson 2 • Digital PID Implementation

Converts continuous PID algorithms to position and velocity forms for digital execution. Addresses discretisation errors and scan-time selection.

Lesson 3 • Control Loop Configuration and Commissioning

Guides the step-by-step process of configuring, testing, and commissioning a control loop on a digital platform. Builds practical implementation competency.

Lesson 4 • Data Acquisition and Historian Systems

Explains how process data is collected, stored, and retrieved for analysis and reporting. Supports performance monitoring covered in the next chapter.

Lesson 1 • Ratio and Split-Range Control

Implements ratio controllers to maintain proportional relationships between streams. Extends control capability to blending and combustion applications.

Lesson 2 • Inferential and Soft-Sensor Control

Estimates unmeasured controlled variables from secondary measurements using process models. Enables control where direct measurement is impractical or costly.

Lesson 3 • Cascade Control

Designs inner and outer loop structures to reject disturbances faster than single-loop control. Builds directly on PID tuning skills from the previous chapter.

Lesson 4 • Feedforward Control

Designs feedforward compensators to cancel measurable disturbances before they affect the controlled variable. Complements feedback control for improved disturbance rejection.

Lesson 1 • Decoupling Control Design

Designs static and dynamic decouplers to eliminate cross-channel interactions. Enables independent single-loop tuning of decoupled channels.

Lesson 2 • Introduction to Model Predictive Control

Introduces MPC as a constraint-handling multivariable control framework. Connects state-space modelling and optimisation to practical MPC implementation.

Lesson 3 • Multivariable Process Interactions

Quantifies loop interactions using the relative gain array and condition number. Establishes the need for multivariable control strategies.

Lesson 4 • State-Space Representation

Formulates multivariable process models in state-space form for analysis and design. Provides the mathematical foundation for modern control methods.

Lesson 1 • Retuning and Controller Redesign

Applies online and offline retuning methods to restore or improve loop performance. Connects diagnostic findings to targeted corrective actions.

Lesson 2 • Control Loop Performance Assessment

Applies statistical and variance-based metrics to quantify loop performance against benchmarks. Identifies underperforming loops for corrective action.

Lesson 3 • Root Cause Diagnosis of Poor Control

Diagnoses causes of poor loop performance including valve stiction, tuning errors, and process changes. Directs maintenance and retuning efforts efficiently.

Lesson 4 • Advanced Process Optimisation

Introduces real-time optimisation and steady-state optimisation frameworks for process economics. Extends control objectives from stability to profitability.