Last modified: 29 Jul 2024 11:46
This course covers both continuous-time and discrete-time (Digital) state-space control of linear systems. It then extends these concepts to nonlinear system modelling and control.
| Study Type | Undergraduate | Level | 5 |
|---|---|---|---|
| Term | First Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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This course starts with a comprehensive introduction to state-space control concepts that include linear state-space models, poles and zeros of a Linear Time Invariant system, observability and controllability. It then introduces the design and optimization of both regulators and estimators via pole-placement; culminating in LQR, LQE and LQE designs.
The course further covers Digital Control concepts and elaborates on how state-space control concepts are impacted in the digital realm. Basic System Identification is also introduced.
The course finally extends the linear state-space control concepts to simple second-order nonlinear systems by introducing linearization, Lyapunov Stability, Equilibrium Points and Phase Plane Portraits. It ends with Gain Scheduling and an introduction to Model Reference Adaptive Control.
| Assessment Type | Summative | Weighting | 30 | |
|---|---|---|---|---|
| Assessment Weeks | 18 | Feedback Weeks | ||
| Feedback |
Graded individual design reports with detailed feedback will be provided. Collective feedback for the entire class will be uploaded as announcement. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to analyse system dynamics via state-space models |
| Procedural | Analyse | Ability to design and analyse state-space controllers in discrete time (digital control) |
| Procedural | Analyse | Ability to generate and analyse state-space models of nonlinear systems |
| Procedural | Analyse | Ability to design and optimize pole-placement compensators |
| Procedural | Evaluate | Ability to evaluate system stability |
| Procedural | Understand | Knowledge and ability to construct state-space models from system’s differential equations. |
| Assessment Type | Summative | Weighting | 70 | |
|---|---|---|---|---|
| Assessment Weeks | 14 | Feedback Weeks | 17 | |
| Feedback |
Graded answer scripts with detailed feedback will be provided. Solutions to the class test will be uploaded. Collective feedback for the entire class will be uploaded as announcements for class test. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to analyse system dynamics via state-space models |
| Procedural | Analyse | Ability to design and analyse state-space controllers in discrete time (digital control) |
| Procedural | Analyse | Ability to design and optimize pole-placement compensators |
| Procedural | Evaluate | Ability to evaluate system stability |
| Procedural | Understand | Knowledge and ability to construct state-space models from system’s differential equations. |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | ||
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback | ||||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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|
||
| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Analyse | Ability to analyse system dynamics via state-space models |
| Procedural | Analyse | Ability to design and optimize pole-placement compensators |
| Procedural | Evaluate | Ability to evaluate system stability |
| Procedural | Analyse | Ability to design and analyse state-space controllers in discrete time (digital control) |
| Procedural | Analyse | Ability to generate and analyse state-space models of nonlinear systems |
| Procedural | Understand | Knowledge and ability to construct state-space models from system’s differential equations. |
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