ACE-Lab CORE Learning Library ACE-Lab CORE Learning Library
Introductory control engineering topics
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No topics foundTry a different keyword, stage or control-engineering term.CComprehend (C)
Introduce the essential ideas, terminology and representations used to describe control systems.
📘Introduction to Control Systems
Control engineering foundations
An introduction to the purpose and basic behaviour of control systems, including open-loop and closed-loop control.
Comprehend Control systems Open and closed loop⚙Key Components of a Control System
Control-system components
An introduction to the roles of the controller, plant or process, sensor, actuator and feedback path within a control system.
Comprehend Components Sensors and actuators▦Block Diagrams to Represent Control Systems
Control-system representation
An introduction to using block diagrams to show control-system components, their connections and the flow of signals.
Comprehend Block diagrams Signal flow〽System Dynamics, Signals and Variables
Dynamic behaviour and signals
A basic introduction to how systems change over time and to the references, outputs, errors, disturbances and manipulated variables used to describe them.
Comprehend System dynamics Signals and variables🎯Requirements
Control requirements
An introduction to expressing control objectives as clear and measurable requirements against which system behaviour can be assessed.
Comprehend Requirements Performance objectivesOOperate (O)
Explain how common control methods, measurements and signals are used in general applications.
⌘Introduction to Microcontrollers
Embedded control
A basic introduction to the role of microcontrollers within digital control systems.
Operate Embedded control Introduction to microcontrollers⏱Sampling and execution rate
Real-time implementation
A basic introduction to sampling, update rates and their effect on digital control.
Operate Real-time implementation Sampling and⌘Digital, analogue and PWM I/O
Embedded I/O
An introductory overview of digital, analogue and pulse-width-modulated signals.
Operate Embedded I/O Digital analogue◉Data acquisition
Measurement
A basic introduction to collecting and interpreting measured control-system data.
Operate Measurement Data acquisition≋Measurement Noise and Basic Filtering
Measurement quality
An introduction to measurement noise, simple smoothing methods and the basic trade-off between noise reduction and added delay.
Operate Measurement noiseBasic filtering◉Sensor calibration
Measurement
An introduction to relating measured values to meaningful engineering quantities.
Operate Measurement Sensor calibration⚙Actuator and motor driving
Actuation
A basic overview of how control commands are converted into actuator inputs.
Operate Actuation Actuator and◉Encoder measurement
Feedback measurement
An introduction to using encoder signals to represent position and speed.
Operate Feedback measurement Encoder measurement⌘Controller Implementation Basics
Controller operation
An introduction to how a controller is repeatedly evaluated within a digital control system, including operating limits and saturation.
Operate Controller implementationLimits and saturation✓Testing and Interpreting PID Control-System Behaviour
Control-system testing
An introduction to applying test inputs, observing the response and interpreting PID control-system behaviour against stated requirements.
Operate TestingResponse interpretationRRefine (R)
Explain how an operating control system is assessed, adjusted and retested to improve its performance and meet its requirements.
✓Performance Assessment, Verification and Validation
Requirements-based evaluation
An introduction to testing reference and disturbance responses, measuring rise time, settling time, overshoot, steady-state error and control effort, and comparing before-and-after behaviour with stated requirements under different operating conditions.
Refine Performance assessment Verification and validation≋Filtering, Sampling and Measurement Refinement
Measurement and digital-control refinement
An introduction to adjusting filtering, sample time and execution rate to improve measurement quality while managing noise, added delay and their effect on control-system behaviour.
Refine Filtering and sampling Measurement quality🎛Controller Tuning, Performance and Stability
Controller refinement
An introduction to adjusting P, PI and PID parameters to improve transient response, steady-state accuracy and disturbance rejection while maintaining stability and accounting for saturation, integral windup and practical operating limits.
Refine Controller tuning Performance and stabilityEEngineer (E)
Introduce mathematical modelling, system identification, analysis, digital control and model-based design methods.
E1Mathematical and Dynamic Modelling
Represent dynamic systems using physical laws, equations and standard continuous-time model forms.
∂Ordinary Differential Equation (ODE) Models
Dynamic modelling
An introduction to representing continuous-time dynamic behaviour using ordinary differential equations and identifying the variables, parameters and initial conditions within an ODE model.
Engineer Dynamic modelling ODE models∂First-principles modelling
First-principles modelling
An introduction to constructing models from physical laws and simplifying assumptions.
Engineer First-principles modelling First principlesℒLaplace transforms
Laplace-domain modelling
A basic introduction to using Laplace transforms in continuous-time control analysis.
Engineer Laplace-domain modelling Laplace transformsℒTransfer functions
Transfer functions
An introduction to representing input-output dynamics using transfer functions.
Engineer Transfer functions Transfer functions∑Block Diagram Algebra
Block-diagram modelling
An introduction to the algebraic rules used to combine and simplify series, parallel and feedback block-diagram structures, including summing junctions and take-off points.
Engineer Block-diagram modelling Block diagram algebra𝑥State-space models
State-space modelling
An introduction to representing dynamic systems using states, inputs and outputs.
Engineer State-space modelling State space⌁Poles, zeros and dynamics
System properties
A basic introduction to the relationship between poles, zeros and system behaviour.
Engineer System properties Poles zerosE2System Identification and Parameter Estimation
Develop suitable model structures from measured data, estimate their parameters and assess how well they represent the physical system.
⌁Introduction to System Identification
Experimental modelling
An introduction to developing dynamic models from measured input-output data, including the identification workflow, experiment design and selection of a suitable model structure.
Engineer Experimental modelling System identification∑Model Order, Fidelity and Uncertainty
Model structure and limitations
An introduction to selecting an appropriate level of model complexity and understanding how parameter variation, measurement limitations and unmodelled dynamics affect model fidelity.
Engineer Model fidelity Model uncertainty⌁Least-Squares Estimation and Model Validation
Parameter estimation and validation
An introduction to estimating unknown model parameters using batch least-squares methods and validating the resulting model by comparing its predictions with independent measured data.
Engineer Least squares Model validation↻Recursive Least Squares
Online parameter estimation
An introduction to updating model-parameter estimates as new measurements arrive, including the role of the covariance matrix and forgetting factor in tracking changing system behaviour.
Engineer Recursive estimation Online identificationE3System Analysis and Model-Based Controller Design
Analyse model behaviour and use time-domain and frequency-domain methods to design controllers.
▦Closed-Loop Modelling and Controller Simulation
Model-based simulation
An introduction to constructing a closed-loop simulation model containing the plant, controller, reference, feedback and disturbances, and using it to examine controller behaviour, compare design choices and assess performance before implementation.
Engineer Closed-loop modelling Controller simulation⌁Continuous-time stability
Stability analysis
An introduction to assessing continuous-time stability using pole locations.
Engineer Stability analysis Continuous time⌁Root locus
Root-locus design
An introduction to how root-locus plots relate controller gain to closed-loop poles.
Engineer Root-locus design Root locus∿Frequency response
Frequency-domain analysis
A basic introduction to analysing system behaviour across a range of frequencies.
Engineer Frequency-domain analysis Frequency response∿Bode plots
Frequency-domain analysis
An introduction to interpreting Bode magnitude and phase plots.
Engineer Frequency-domain analysis Bode plots⌁Stability margins
Robustness
A basic overview of gain margin, phase margin and relative stability.
Engineer Robustness Stability margins🎛Model-based PID design
Controller design
An introduction to designing PID controllers using a mathematical model.
Engineer Controller design Model based🎛Lead and lag compensation
Compensator design
A basic introduction to lead and lag compensator structures.
Engineer Compensator design Lead andE4Discrete-Time Modelling and Digital Control
Represent, analyse and design sampled-data and discrete-time control systems.
⏱Discrete-Time Systems and Continuous-to-Discrete Conversion
Digital control foundations
An introduction to sampled-data and discrete-time systems, including how continuous-time models are converted into discrete forms for analysis, simulation and digital controller design.
Engineer Discrete-time systems Discretisation⏱Z-transforms
Z-domain modelling
A basic introduction to using Z-transforms in discrete-time control analysis.
Engineer Z-domain modelling Z transforms⏱Discrete transfer functions
Discrete models
An introduction to representing sampled systems using discrete transfer functions.
Engineer Discrete models Discrete transfer⏱Difference equations
Discrete implementation
A basic introduction to representing discrete systems using recursive equations.
Engineer Discrete implementation Difference equations⏱Z-Plane Stability and Performance
Discrete stability and response
An introduction to assessing discrete-time stability from pole locations in the Z-plane and relating those locations to response speed, damping, oscillation, overshoot and settling behaviour.
Engineer Z-plane analysis Stability and performance⏱Digital controller design
Digital controller design
A basic introduction to designing controllers for discrete-time systems.
Engineer Digital controller design Digital controllerE5Model-Based Design, Implementation and Validation
Consolidate the selected design, prepare it for implementation, generate code and compare deployed behaviour with model predictions.
🎯Design from requirements
Requirements-led design
An introduction to connecting control requirements with modelling and design choices.
Engineer Requirements-led design Design from▶Design-space exploration
Design exploration
A basic overview of comparing controller structures and parameter choices.
Engineer Design exploration Design space✓Model verification
Verification
An introduction to checking whether a model-based design meets stated requirements.
Engineer Verification Model verification↧Implementation effects
Non-ideal behaviour
A basic introduction to delays, quantisation, saturation and other implementation effects.
Engineer Non-ideal behaviour Implementation effects🎛Implementation-ready controller
Deployment preparation
An overview of the form a controller must take before digital implementation.
Engineer Deployment preparation Implementation ready⌘Automatic code generation
Code generation
A basic introduction to the role of automatic code generation in model-based design.
Engineer Code generation Automatic code✓Simulation-to-hardware validation
Model-hardware comparison
An introduction to comparing simulated behaviour with later practical results.
Engineer Model-hardware comparison Simulation to∑Model-based design iteration
Iterative design
An introduction to the iterative relationship between requirements, models and control design.
Engineer Iterative design Model based
