AEE483 AUTOMATIC CONTROL SYSTEMS II
| Course Code: | 5720483 |
| METU Credit (Theoretical-Laboratory hours/week): | 4 (4.00 - 0.00) |
| ECTS Credit: | 5.0 |
| Department: | Aerospace Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. HALİL ERSİN SÖKEN |
| Offered Semester: | Fall Semesters. |
Course Objectives
By the end of AE483 Automatic Control II, students will:
- Understand and apply state-space representations for dynamic systems.
- Analyze controllability and observability of linear systems and their impact on system design.
- Design and implement state feedback controllers using pole placement and observer-based methods.
- Apply Lyapunov stability theory to analyze the stability of linear systems.
- Develop and tune optimal control laws, particularly Linear Quadratic Regulator (LQR).
- Understand and implement state estimation techniques, including Kalman filtering.
- Gain hands-on experience with modern control applications through simulations and a term project.
Course Content
State equations, canonical forms, eigenvalues, eigenvectors, stability, controllability, observability; state space approach to control system design, state variable feedback, eigenstructure assignment, state observation, model following control, introduction to optimal control, linear quadratic regulator.
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
- Convert a given system model into state-space form and analyze its dynamic properties.
- Evaluate the controllability and observability of a system using mathematical criteria.
- Design a state feedback controller to achieve desired closed-loop performance.
- Apply Lyapunov’s direct method to determine the stability of linear systems.
- Solve the Algebraic Riccati Equation (ARE) and design LQR controllers for optimal performance.
- Implement state estimation techniques using full-order and reduced-order observers.
- Apply the Kalman filter for real-time state estimation in noisy environments.
- Utilize MATLAB/Python to simulate and analyze state-space controllers.
- Work collaboratively on a term project, applying modern control techniques to real-world aerospace problems.
Program Outcomes Matrix
| Contribution | |||||
| # | Program Outcomes | No | Yes | ||
| 1 | An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics | ✔ | |||
| 2 | An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors | ✔ | |||
| 3 | An ability to communicate effectively with a range of audiences | ✔ | |||
| 4 | An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts | ✔ | |||
| 5 | An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives | ✔ | |||
| 6 | An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions | ✔ | |||
| 7 | An ability to acquire and apply new knowledge as needed, using appropriate learning strategies | ✔ | |||