Study Guide 2015-2016

ASE-5056 Optimal and Robust Control with Matlab, 8 cr

Additional information

Suitable for postgraduate studies

Person responsible

Terho Jussila, Risto Ritala, Robert Piche

Lessons

Implementation 1: ASE-5056 2015-02

Study type P1 P2 P3 P4 Summer
Lectures
Excercises
Assignment
Laboratory work




 




 
 3 h/week
 3 h/week
 6 h/per
 0 h/week
+3 h/week
+3 h/week
+8 h/per
+3 h/week




 

Lecture times and places: Monday 9 - 11 SD207 , Monday 8 - 11 , Monday 8 - 9 SD205 , Tuesday 14 - 17 SD207 , Wednesday 14 - 17 SD207

Requirements

Written exam (or a set of written sub-exams) plus a PC Exam plus 7 PC sessions (each of 120 minutes) plus a practical LAB of 2-3 hours.
Completion parts must belong to the same implementation

Learning Outcomes

After the course the student should be able to use Matlab, Simulink, Control System Toolbox and Symbolic Toolbox to design a H2/LQ (Linear Quadratic) and LQG (LQ Gaussian) control law for a LTI (Linear Time-Invariant) state space system, analyze robust stability of the overall system in both classical and modern ways; can propose implementations; can use Matlab and the toolboxes for both time domain modeling, simulation and various other analyses of various MIMO LTI systems, including nominal and robustness analyses; knows several quadratic performance indices and their properties; understands special features and challenges of MIMO control design; can use both state space and transfer function models in an appropriate way and make conversions between model types; can create simple Matlab tools when Toolboxes are not providing suitable ones.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Time domain simulation of various model types with Simulink, Control System Toolbox and tools of the core Matlab.  Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.  S functions of Simulink. Creating and masking sub-systems. Use of ode45 and dde23. 
2. Matlab and Control System Toolbox for effective modelling: equilibriums, linearization, least squares, model reduction, model type conversions, building models from sub-system models.  Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.  Solvers and optimizers. 
3. Basics of Linear Time Invariant models of MIMO systems: example responses, stability, controllability, observability, transfer function matrix, frequency response.  Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.   
4. Quadratic performance indices and signal norms, even for time-delay systems and including time-weighting. Linear Quadratic deterministic state-feedback control and quadratic optimal parametric control.  Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.   
5. Classical and modern studies of robust stability: stability margins for MIMO systems and studies of unstructured uncertainty.  Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.   
6. Vector random processess in time and frequency domain. Identification, spectral factorization. Mean and variance calculus, variance minimization. Stochastic regulator, Kalman filtering, LQG control.   Both DT (Discrete-Time) and CT (Continuos-Time) studies are available so that one of them is primary, the other is secondary. The decision will be made for every implementation separately.   
7. Improving reliability of the computations.     

Instructions for students on how to achieve the learning outcomes

Usual.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Additional information Examination material
Book     Nomen Nescio       The main course book will be specified separately for each particular implementation.   Yes   
Summary of lectures     Lecturer       The lecture notes/slides will be specified separately for each particular implementation.   Yes   

Prerequisites

Course Mandatory/Advisable Description
ASE-1130 Automaatio Mandatory   1
ASE-1251 Järjestelmien ohjaus Mandatory   1
ASE-1257 Introduction to Control Mandatory   1

1 . One of the ASE courses 1130, 1251, 1257 is necessary if the student is not mastering the content of such a course otherwise.



Correspondence of content

Course Corresponds course  Description 
ACI-21086 Control System Design with Matlab, 5 cr +
ACI-42066 Robust Control, 5 cr +
ASE-5056 Optimal and Robust Control with Matlab, 8 cr
ACI-42086 Optimal and Robust Control System Design with Matlab, 7 cr  
ASE-5056 Optimal and Robust Control with Matlab, 8 cr ASE-5056 Optimal and Robust Control with Matlab, 8 cr  
ASE-5056 Optimal and Robust Control with Matlab, 8 cr ACI-21086 Control System Design with Matlab, 5 cr  

Last modified 19.12.2015