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Syllabus for

Academic year
MKM095 - Model based controls systems
 
Owner: TAUTA
4,0 Credits (ECTS 6)
Grading: TH - Five, Four, Three, Not passed
Level: A
Department: 32 - ELECTRICAL ENGINEERING


Teaching language: Swedish

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0100 Laboratory 1,0 c Grading: UG   1,0 c    
0200 Examination 3,0 c Grading: TH   3,0 c   17 Mar 2007 pm V,  20 Jan 2007 pm V,  30 Aug 2007 am M

In programs

TAUTA AUTOMATION AND MECHATRONICS ENGENEERING, Year 4 (elective)

Examiner:

Professor  Bo Egardt



Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

Introductory control course.

Aim

Aim and Goal:
The aim of the course is to give knowledge in control useful for
problems of larger complexity than a simple control loop. By
introducing state space descriptions new possibilities arise:
* Insights of dynamic properties of complex, eg nonlinear and
multi-input and multi-output, systems by computer simulation.
* Give design methods where the performance of the closed loop system
is formulated as a criterion which should be optimized (optimal
control).
* Improved accuracy and reliability by using estimation techniques,
eg, non measurable signals are estimated using other signals and
model of the system. With these techniques it is also possible to
detect faults among the sensor signals.
Insights of the techniques to estimate the state of a system using a
model and available sensor signals, and to use the estimate for
closed loop control. Stochastic descriptions of disturbances and
noise are used and methods to minimize their influence are introduced.

Content

Tools for modeling, analysis and design of dynamic systems: Modeling of linear and
nonlinear systems. Tools for nonlinear systems, phase plane and
describing function. Computer simulation. Linearisation. Linear state
space techniques for continuous and discrete time systems. The
solution of the state space description, sampling of continuous time
systems, dead time. Analysis of properties of dynamic systems,
features such as stability, observable and controllable systems,
duality. Change of state space representation and canonical forms.
State feedback: designed by closed loop specifications, integral
action and feed forward compensation of the reference signal. Design
by quadratic criteria functions, linear quadratic optimal control
(LQ).
State estimation using observers: design by pole placement and by
criterion minimization with stochastic assumptions on disturbances
and noise (Kalman filter).
Control based on estimated states: Linear Quadratic Gaussian
controller (LQG). Robustness and sensitivity of LQG controllers.
Design and implementation of continuous and discrete time systems
using Matlab and Control System Toolbox.
Application example: Electro-mechanical actuators, navigation and
control of autonomous vehicles, active damping of disturbances and vibrations

Hand-in Assignments:
1) Nonlinear systems and discrete time simulation
2) Analysis and design using Matlab

Laboratory exercises:
Modeling and control of a robot arm

Organisation

Lectures and problem solving sessions.
Hand-in assignments and laboratory session (mandatory).

Literature

B.Schmidtbauer, Modellbaserade reglersystem (Studentlitteratur, 1999, in Swedish) or alternative to be defined.

Examination

Written exam.


Page manager Published: Mon 28 Nov 2016.