ee-m110 2006/7, ef l17 1/12, v1.0 lecture 17: armax and other linear model structures dr martin...

14
EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: [email protected] Telephone: 0161 306 4672 http://www.eee.manchester.ac.uk/intranet/pg/ coursematerial/

Upload: nadia-biller

Post on 31-Mar-2015

215 views

Category:

Documents


1 download

TRANSCRIPT

Page 1: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 1/12, v1.0

Lecture 17:ARMAX and other Linear Model Structures

Dr Martin Brown

Room: E1k, Control Systems Centre

Email: [email protected]

Telephone: 0161 306 4672

http://www.eee.manchester.ac.uk/intranet/pg/coursematerial/

Page 2: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 2/12, v1.0

L17: Resources & Learning Objectives

Core texts• Ljung, Chapters 2, 3 & 4

In this lecture we’re looking at the basic ARMAX model structure and considering

1. How it differs from ARX representation

2. What disturbance signals can be modelled

3. How the parameters are represented and estimated

4. Other discrete time polynomials models

Page 3: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 3/12, v1.0

Page 4: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 4/12, v1.0

Not Gaussian, Additive Disturbances

The disturbances are characterised by the fact that the value is not known beforehand, however it is important for making predictions about future values.

Use a probabilistic framework to describe disturbances, and generally describe e(t) by its mean and variance (iid).

The modelling of the transfer function h, can give dynamic disturbance terms:

where is small and r~N(0,2)

0

( ) ( ) ( )k

v t h k e t k

0 with probability 1( )

with probability e t

r

v(t)

Page 5: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 5/12, v1.0

Page 6: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 6/12, v1.0

Page 7: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 7/12, v1.0

Page 8: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 8/12, v1.0

Page 9: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 9/12, v1.0

Example: ARMAX Model

First order model

We assume that e(t) is normal, iid noise. This is not true for v(t) = e(t)+0.2e(t-1), hence we can’t use an ARX model and must use a first order ARMAX system.

The poles of the disturbance->output and the control->output are both given by A=1-0.5q-1

The zeros of the disturbance->output are given by C=1+0.2q-1

The zeros of the control->output are given by B=q-1

In forming a prediction, we use e(t)=y(t)-y(t), hence the model is non-linear in its parameters.

( ) 0.5 ( 1) ( 1) ( ) 0.2 ( 1)y t y t u t e t e t

^

Page 10: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 10/12, v1.0

Page 11: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 11/12, v1.0

Page 12: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 12/12, v1.0

Page 13: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 13/12, v1.0

L17 Summary

Whilst much of this course has concentrated on a simple ARX model, this is very limiting in the type of disturbances that can be modelled.

ARMAX, Output Error, Box-Jenkins … models all generalise the basic ARX transfer function and can disturbance/noise terms with dynamics

However, the parameter estimation problem is no longer a quadratic optimization process and iterative algorithms must be used.

Page 14: EE-M110 2006/7, EF L17 1/12, v1.0 Lecture 17: ARMAX and other Linear Model Structures Dr Martin Brown Room: E1k, Control Systems Centre Email: martin.brown@manchester.ac.uk

EE-M110 2006/7, EF L17 14/12, v1.0

L17 Lab