Analysis and design of sampled-data systems, extraction of discrete-time dynamic models from experimental data, and implementation of dynamic compensators on digital processors. In-depth design experience with LQR optimal control and an introduction to Kalman filtering. Realistic design problems with numerical simulations of practical implementations.
The proposed course provides a hands-on understanding of fundamental implementation issues in the design of control systems implemented on digital processors. The course emphasizes the use of software tools for the analysis and design of practical controller solutions.
5554 or 5544 or AOE 5744 or AOE 5754 or ECE 5744 or ECE 5754
Prior to taking this course, students must have a solid background in classical control theory (which is taught at the undergraduate level), as well as a solid background in linear systems theory (which is only taught at the graduate level). Completion of assigned work in this course requires a prerequisite knowledge of state-feedback controller design, output-feedback controller design, and general linear systems theory. These topics are only taught at the graduate level, and are covered by any one of the prerequisite courses listed above.
Percentage of Course
|1. Sampled data systems||10%|
|2. Digital controller architectures and anti-aliasing/anti-imaging||10%|
|3. Z-transform and difference equations||10%|
|4. Continuous-to-discrete transformations (SISO and MIMO)||5%|
|5. Discrete state-space, IIR, and FIR realizations||10%|
|6. Frequency response and transfer functions matrices||5%|
|7. Characteristic Equation, Eigenvalues, and stability criteria||5%|
|8. Discrete time full state feedback and output feedback design||10%|
|9. LQR Optimal Control||15%|
|10. Kalman Filtering and stochastics||10%|
|11. System Identification||10%|