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Course Information
The course is an introduction to dynamic systems and their modeling via differential equations as well as their feedback control. Model linearization and analysis of classic control systems in the time and frequency domains are discussed using transfer functions. Design techniques are practiced for linear time-invariant feedback control systems using root locus and bode plot techniques, considering various factors including system robustness and stability through Routh-Hurwitz and Nyquist criteria.
Course Goals
After completion of the course, successful students should be better able to:
- demonstrate competency in modeling and analysis of continuous, linear time-invariant closed-loop control systems, including specific tasks of constructing analytical models and studying their stability and dynamic response;
- use proper techniques of linearizing system models in order to utilize them in designing feedback control mechanisms for real-life systems, and understand the effect of model linearization on their performance;
- systematically carry out steps of designing controllers for linear time-invariant systems, including PID and Lead-Lag networks, in order to meet the desired specifications;
- verify and validate the performance of designed controllers in ensuring stability, meeting the specifications, and handling external disturbances, model uncertainties and sensory noise;
- demonstrate proficiency in using Matlab/Simulinkรข for synthesis and analysis of control systems; and
- understand challenges of designing controllers for real-life systems and how to ensure critical features such as system stability and robustness through several laboratory experiments.