48580 Control Studio B
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Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade, no marksRequisite(s): 48560 Control Studio A
Recommended studies: previous study of simple control systems using transfer functions and state-variables is essential
Description
Autonomous control systems play an essential role in modern society. Classical linear control approaches can be used to govern (linear) systems where normally one variable needs to be controlled (e.g., room temperature in an air-conditioning system, water level in a tank, etc.). However, there are many modern complex process and applications that require control systems to autonomously govern several variables at the same time, e.g., power systems, industrial process, aircraft, electric vehicles, etc. Moreover, some systems can even present nonlinear dynamics, which further complicate the control process design. For this reason, more sophisticated control techniques (compared to classical methods learned in previous subjects) need to be designed and implemented to govern more complex systems.
This studio subject focuses on aspects of advanced control engineering design for multivariable systems. The overall aim of this studio is to provide a rich and attractive practice-based learning environment for electrical engineering students to deeply learn and become professionally competent in advanced control engineering. Students will work from concept stage to realisation of product, thus, striking a balance between theory and practice. To realise these aims, this studio focuses on the methods of reflective design practice, teamwork, mentoring, and deep learning techniques, including immersion in difficult problems. The subject allows students to move towards senior roles in teams, expects students to become accomplished in reflection, and demonstrate application of modern and advanced control engineering skills, with an accent on design, simulation and practical validation.
Subject learning objectives (SLOs)
Upon successful completion of this subject students should be able to:
| 1. | Mathematically model, simulate and analyse multivariable (not necessarily linear) systems for control purposes. (D.1) |
|---|---|
| 2. | Propose, design and validate advanced control strategies to create a multivariable autonomous control system conforming to given specifications. (C.1) |
| 3. | Identify model uncertainties and/or disturbances that can affect the control system performance in order to enhance robustness. (D.1) |
| 4. | Translate theoretical advanced control designs into control algorithms to achieve a practical implementation of the developed autonomous multivariable control system. (D.1) |
Course intended learning outcomes (CILOs)
This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):
- Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
- Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
Contribution to the development of graduate attributes
Engineers Australia Stage 1 Competencies
This subject contributes to the development of the following Engineers Australia Stage 1 Competencies:
- 1.3. In-depth understanding of specialist bodies of knowledge within the engineering discipline.
- 2.1. Application of established engineering methods to complex engineering problem solving.
- 2.2. Fluent application of engineering techniques, tools and resources.
- 2.4. Application of systematic approaches to the conduct and management of engineering projects.
Teaching and learning strategies
This is a studio-based subject that duplicates industrial and research development practices suited to small projects. In small self-managed teams, students are guided through the early stages of team formation and agile project planning before adopting greater autonomy for the remainder of the project. Students engage in self-learning. Teams are aided and guided by tutors experienced in control engineering. To encourage peer learning all teams formally critique the work of another team at significant stages during the project life cycle. To encourage high technical standards, high achievement and peer learning, all teams develop a system from specified requirements but are free to decide how those requirements can be implemented to achieve more beneficial solutions.
Students are expected to attend studio sessions to get common knowledge in control engineering. The studio sessions are designed as building blocks of learning during which time tutors provide weekly feedback about progress, intended activities and achievements to date. Formal assessment of the project outcomes and deliverables occurs at mid and end of session. Early session team formation and skill development activities provide opportunities for feedback about essential team and technical skills.
Content (topics)
- Modelling and simulation of multivariable systems
- Linearisation of multivariable nonlinear systems
- System model identification of multivariable systems
- State-variable feedback controller and observers
- Multivariable nonlinear stability analysis in the Lyapunov sense
- Optimal control and filtering of multivariable systems
- Robust control of multivariable systems
- Nonlinear control
Assessment
Assessment task 1: Project requirements and solution design rationale
| Intent: | To demonstrate the ability to understand and explain control systems requirements and propose a feasible solution design. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): D.1 |
| Type: | Presentation |
| Groupwork: | Group, group assessed |
| Weight: | 5% |
| Length: | 10 minute presentation |
Assessment task 2: Interim project demonstration
| Intent: | To demonstrate knowledge of state feedback control of multivariable systems, including modelling, analysis, control design and computational simulation. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Demonstration |
| Groupwork: | Group, individually assessed |
| Weight: | 15% |
| Length: | 10 minute presentation |
Assessment task 3: Final project demonstration
| Intent: | To demonstrate practical skills in implementation of advanced control strategies, including the design process and performance evaluation of real-world dynamic systems under control. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Project |
| Groupwork: | Group, individually assessed |
| Weight: | 30% |
| Length: | 15 minute presentation |
Assessment task 4: Final project report
| Intent: | To demonstrate understanding of the challenges and requirements of autonomous advanced control systems design. Moreover, the methods, tools and resources to achieving their objectives are also evaluated in this report. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Project |
| Groupwork: | Group, group and individually assessed |
| Weight: | 20% |
| Length: | 10,000 words |
Assessment task 5: Assignments
| Intent: | To demonstrate theoretical knowledge of advanced control systems design. |
|---|---|
| Objective(s): | This assessment task addresses the following subject learning objectives (SLOs): 1, 2, 3 and 4 This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs): C.1 and D.1 |
| Type: | Exercises |
| Groupwork: | Individual |
| Weight: | 30% |
| Length: | 5000 words for each assignment |
Minimum requirements
To pass this subject, students must achieve an overall mark of 50% or greater.
Required texts
- Goodwin, Graebe, & Salgado, “Control System Design,” Prentice Hall, 2001
- Franklin, G. F., Powell, J. D., & Emami-Naeini, A., “Feedback Control of Dynamic Systems,” 7th Ed., Prentice Hall, 2015
Recommended texts
- Khalil, H.K., “Nonlinear Control,” Pearson, 2015
- Nise, N.S., “Control System Engineering,” 6th Ed., John Wiley, 2011
- Dorf, & Bishop, “Modern Control Systems,” 13th Ed., Pearson, 2016
- Goodwin, de Dona, Seron, “Constrained Control and Estimation”, Springer, 2005
- Wang, L., “Model Predictive Control System Design and Implementation Using MATLAB®”, Springer, 2009