Computer Control in State-Space

Recommended Prerequisites

Digital Control; Probabilistic Machine Learning; Signal Processing  

Teaching Methods

Lectures involving detailed presentation of concepts, principles and theories that constitute the materials of the curricular unit. In these classes, there is room to solving exercises with active participation of students.

Laboratory classes where students exercise the concepts taught in theoretical lectures by performing simulation studies, in Matlab/Simulink, and pratical work with real processes. Additionally, students have access to a wide range of theoretical/practical problems solved and others for resolution.

Learning Outcomes

Objectives: Provide students with the main concepts, principles and theories that enable the analysis and design of linear computer-controlled systems using state-space techniques. In this context, it is included the analysis and synthesis of controllers with state observers: state observers for deterministic disturbances and stochastic optimal state observers for random disturbances.

The curricular unit includes lab classes for conducting simulation studies, using Matlab/Simulink, and design of digital controllers applied to real processes.

Skills to develop: It is intended that students acquire skills in analysis and synthesis, formulation and problem solving, critical thinking, independent learning and ability to apply theoretical concepts in solving practical problems.  

Work Placement(s)

No

Syllabus

MODULE  I – Deterministic disturbances

I. State observers; Design of controllers with state observers;

II. Models of deterministic disturbances. Regulation with augmented state observers (process and disturbance); adding integral action.

III. Servocontrol with and without state observers; servocontrol with integral action: with augmented state-observer and by internal-model structures (without observer). 

MODULE II – Stochastic disturbances

I. Models of stochastic  disturbances.

II. Optimal filters in discrete time: linear applications (Kalman filter) and nonlinear applications (EKF, particle filters).

III. State-space control design with state observers based on optimal filters

MODULE III

I. Introduction to optimal control design methods: a state-space approach  (e.g, LQR and LQC). 

Head Lecturer(s)

Urbano José Carreira Nunes

Assessment Methods

Assessment
Laboratory work or Field work: 20.0%
Exam: 40.0%
Frequency: 40.0%

Bibliography

 

• K.J. Astrom, and B. Wittenmark (1997) - Computer-Controlled Systems: Theory and Design, 3ª Ed., Prentice-Hall.

• Franklin, G.P., Powell, J., and Workman, M. (1994) - Digital Control of Dynamic Systems, 3ª Ed., Addison-Wesley.

• M. Grewal, and Angus P. Andrews (2001) - Kalman Filtering: theory and Practise using Matlab, John Wiley & Sons, Inc.

• S.M.Bozic (1979) – Digital and Kalman Filtering, Edward Arnold.

• Nunes, U. (2020) – Controlo Digital: Exercícios Resolvidos, Exemplos em Matlab/Simulink (apontamentos), DEEC-FCTUC.

• Nunes, U. (2020) – Slides das aulas teóricas de Controlo Digital e de Projeto de Controlo Digital, DEEC-FCTUC.