CMPE Degree: This course is Not Applicable for the CMPE degree.
EE Degree: This course is Not Applicable for the EE degree.
Lab Hours: 0 supervised lab hours and 0 unsupervised lab hours.
Technical Interest Group(s) / Course Type(s): Systems and Controls
Prerequisites: ECE 6550
Catalog DescriptionMethods of parameter estimation and adaptive control for systems with
constant or slowly-varying unknown parameters. MATLAB design projects
emphasizing applications to physical systems.
Textbook(s)Robust Adaptive Control
Student OutcomesIn the parentheses for each Student Outcome:
"P" for primary indicates the outcome is a major focus of the entire course.
“M” for moderate indicates the outcome is the focus of at least one component of the course, but not majority of course material.
“LN” for “little to none” indicates that the course does not contribute significantly to this outcome.
1. ( Not Applicable ) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2. ( Not Applicable ) 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. ( Not Applicable ) An ability to communicate effectively with a range of audiences
4. ( Not Applicable ) 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. ( Not Applicable ) 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. ( Not Applicable ) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7. ( Not Applicable ) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
Strategic Performance Indicators (SPIs)
1. Lyapunov Stability Theory
a. Invariant Set Theorems
b. Barbalat’s Lemma
c. SPR Lemma
d. Nonlinear Time-Invariant and Time-Varying Systems
2. Parameter Estimation
a. Estimation Error Criteria
b. Gradient Methods
c. Least-Squares Methods
3. Model Reference Adaptive Control
a. Scalar Case
b. State Feedback Design
c. Output Feedback Design
4. Robust Adaptive Control
a. Convergence Guarantees
b. Instability Phenomena
c. Modifications for Robustness
5. Adaptive Control of Nonlinear Systems (Additional Topics)
a. Systems with Deadzone, Backlash or Hysteresis
b. Neuro-Adaptive Control
c. Adaptive Control via Linearization
d. Adaptive Control via Backstepping
e. Concurrent Learning
f. Repetitive Control / Iterative Learning Control