Control Systems using Simulink
Summary
Analytically solving differential equations representing dynamic systems can sometimes distract from the physical implications of the model. In this module, the dynamic equations of a DC motor are used as a tutorial for inputting ordinary differential equations into Simulink. Speed control of the motor is done via proportional-integral-derivative (PID) control and an adaptive control scheme. The implications of using different controller types, gains and operating motor voltages are explored. Finally, the longitudinal linearized model of an aircraft in level flight is used to investigate the forward velocity, rate of climb and pitch rate of an aircraft subjected to an elevator input. As an assignment, a PID and adaptive control schemes are implemented and compared.
CollapseLearning Goals
Students will engage in model development and a practical approach to control system implementation. Experimenting in the Simulink environment will introduce an 'experimenter mindset' in a virtual space by visualizing equations and seeing the impact of variables via scopes. The concept of non-linear equations will be introduced along with the methods employed for control of these systems. The exercise learning outcomes are detailed below.
| Learning Outcome | Description | Cognitive Level (Bloom's Taxonomy) | Focus |
| LO1 | Construct and simulate a control system model in Simulink using appropriate modeling conventions and tools. | Apply / Create | Procedural skill and tool proficiency |
| LO2 | Implement and tune PID and MRAS controllers, demonstrating understanding of control theory principles and system response behavior. | Analyze / Evaluate | Analytical design and validation |
| LO3 | Evaluate the dynamic response of the aircraft model and control system through systematic experimentation and interpretation of results. | Analyze / Evaluate | Critical interpretation and validation |
| LO4 | Modify and extend the system equations to incorporate disturbances or non-linearities, demonstrating understanding of physical system behavior. | Create / Evaluate | Conceptual modeling and real-world reasoning |
| LO5 | Communicate findings effectively in a structured technical report, integrating simulation results, analysis, and conclusions. | Evaluate / Create | Technical communication and synthesis |
Context for Use
This module is appropriate for students in the final year of their engineering program, having completed courses in 'Dynamic Systems' and 'Control Systems Design'. MATLAB and Simulink Onramp self-paced courses should be completed prior to this module. Students will be required to engage in 5 exercises to obtain the plots given in the module document. The exercises are to be done in the laboratory under the supervision of the teacher or assistant.
Description and Teaching Materials
The module with the exercises and preambles is provided in a pdf file. The Simulink files for the exercises (solutions) are provided for educators. The solution to the assignment is also provided along with a grading rubric. Description of files:
Control Systems using Simulink.pdf – This is the module that guides the students through the exercises. The assignment is given at the end of the module.
Assignment rubric.pdf – This a grading rubric for assessing the Simulink files for the assignment.
MATLAB files folder – Contains the files used to create the plots for the exercises in the module. The assignment's Simulink files are also provided.
Control Systems using Simulink (Acrobat (PDF) 3.1MB Nov5 25)
MATLAB Files (Zip Archive 371kB Sep30 25)
Teaching Notes and Tips
This module should be done around 5 weeks into the semester, allowing students to complete the MATLAB and Simulink Onramp courses. If educators are unsure of students' modelling and control systems proficiency, the 'spring-mass-damper' recap in the module can be done in MATLAB. Students can enter the transfer function in a script file and compare the model output to analytical solutions for step and sinusoidal inputs. The entire module can be done over 2 – 3-hour sessions, ensuring that all students have completed the exercises. The first session can stop at exercise 3, and exercises 4, 5 and task 1 of the assignment can be done in the second session. Based on the pace of the class, the additional tasks at the end of exercise 3 (session 1) or task 2 of the assignment (session 2) can be included.
Teachers and teaching assistants should be present whilst the students work on the exercises. The physical meanings of the plots should be explained – for example, the saturation block limiting voltage to the motor. To prepare for a session, educators can download and experiment with the Simulink models to unlock other perspectives.
Assessment
The assignment at the end of the module assesses students' proficiency in developing, analyzing, and evaluating control system models using Simulink. Proficiency is demonstrated through the ability to construct accurate models, implement and tune control strategies, interpret system responses, and justify design choices using appropriate theoretical reasoning.
Students are required to submit their Simulink models along with a technical report that documents their modeling process, controller implementation, and critical analysis of results. The report also includes a reflection component, in which students connect their computational work to the underlying physical system behavior and discuss the insights gained through simulation.
Assessment is based on a detailed rubric aligned with the stated learning outcomes (LO1–LO5). The rubric emphasizes higher-order thinking skills such as analysis, evaluation, and synthesis, while also recognizing procedural proficiency in model construction and control system implementation. Marks are awarded for modeling accuracy, analytical depth, experimental interpretation, realism of system modifications, report quality, and reflection on learning.
Assignment rubric.pdf (Acrobat (PDF) 63kB Nov3 25)