PME 5201-0

Brief

The aim of this course is to develop familiarity with the fundamental concepts of linear system theory and to become proficient in the mathematical techniques and tools used to evaluate the intrinsic dynamic properties of linear lumped parameter dynamic systems, and to predict the system's response to specified inputs.

Description

Course keywords: Dynamic systems; Input-output desc<x>ription; State-variable desc<x>ription; Controllability; Observability; State Feedback; State Estimation A. Course Description: The aim of this course is to develop familiarity with the fundamental concepts of linear system theory and to become proficient in the mathematical techniques and tools used to assess the intrinsic dynamics of lumped parametric dynamic systems. The discussion is limited to continuous-time models of physical systems and discrete-time models of sampled data systems. Taking real-world engineering systems as examples, a better understanding of the relationship between mathematical models and physical systems can lead to a deeper insight into the internal dynamics of the system. Both the input-output description/transfer function representation and the state variable description are considered. This course will use MATLAB to perform the necessary calculations. B. Textbooks: There is no required textbook. C. References: 1) C-T Chen, Linear System Theory and Design, HRW, 1984. 2) Robert H. Cannon, Dynamics of Physical Systems, 1967. D. Teaching Method: Use PowerPoint presentations and chalkboards for lectures. E. Course Outline: 1. Mathematical model representation of lumped parametric dynamic systems 2. Equilibrium state and linearization 3. Input-output description and transfer functions 4. Output response of linear time-invariant systems 5. Discrete-time modeling and analysis of sampled-data systems 6. State-variable description of continuous-time systems 7. Analysis of linear state equations/eigen analysis and modal decomposition 8. Stability, controllability, and observability of continuous-time linear dynamic systems 9. Discrete-time state-variable description of sampled-data systems 10. Stability, controllability, and observability of discrete-time linear dynamic systems 11. State feedback/Pole placement and state estimators 12. Augmented state estimators (disturbance observer and real-time estimation of process parameters) F. Grading: Homework 25% Exam I 25% (October 03) Exam II 25% (November 21) Exam III (Final Exam) 25% (December 19) G. Ethical Statement on Generative Artificial Intelligence: Prohibition on Use. The course instructor believes that it is not appropriate to use generative AI in the learning of this course. Students enrolled in this course should note that the use of AI models to generate assignments, reports, or personal reflections is strictly prohibited. If such use is detected, the course instructor, the university, or the relevant authority reserves the right to re-evaluate or not grade the assignment or report. Students who enroll in this course are deemed to have agreed to the above Ethics Statement at the time of course selection.

Timetable

Remarks

動機系碩士班電機控制組必選、博士班資格考科目

Restrictions

Compulsory

Elective

Cross Discipline

First Specialization

Second Specialization