Optimal and Adaptive Control
Master's degree in Electrical Engineering (specialization in Control and Industrial Electronics)
6 ECTS; 1º Ano, 2º Semestre, 28,0 T + 28,0 PL + 5,0 OT + 2,0 O
General knowledge of control, including most common techniques and methods in MIMO control (multivariable) and state-space approaches; analysis and design skills through practical applications of the different techniques such as state estimate using Kalman Filter; design optimal and adaptive systems
1 - Introduction and Reviews: Controllability and observability; design of state feedback and output feedback control: Ackermann's formula.
2 - Regulator Design and Reference Following: Controller with state observer; Predictor estimator; Current estimator. Reference inputs for full-state feedback systems; reference input with estimators; reference input with output error command; comparison of the estimator structure and classical methods.
3 - Disturbances and Control by State Augmentation: Disturbances estimation; Control by state augmentation, including the process model; Control by state augmentation, including the disturbances model; Integral control action.
4 - Adaptive Control: Least Squares Method; parameter estimate.
5 - MIMO Systems and Optimal Control: Time-varying optimal control; Linear quadratic regulator (LQR) steady-state optimal control; Optimal estimation based on Kalman Filter; Multivariable Control Design.
6 - Brief introduction to system identification techniques.
Exam (50%) practical coursework (50%).
- Astrom, K. e Wittenmark, H. (1997). Computer-controlled systems: theory and design. USA: Prentice-Hall
- Franklin, G. e Powell, D. e Workman, M. (1998). Digital Control of Dynamic Systems. USA: Addison-Wesley
- Ogata, K. (1994). Discrete-time Control Systems. USA: Prentice-Hall
Method of interaction
Lectures supported by illustrative cases. Theoretical-practical lessons
focused on concept application and problem-solving. Practical works proposed to the students.
Software used in class
Matlab / Simulink