Main

!! MATLAB State Space and Transfer Function Models

The model forms covered in this class include continuous and discrete state space and the Laplace domain. A brief tutorial on converting between these model forms in given in the video below:

* %list list-page% [[Attach:Lecture31_handout2.pdf | State Space Exercise]]

## Lecture Notes 32

## Main.LectureNotes32 History

Hide minor edits - Show changes to output

Changed lines 20-25 from:

!!!! ~~Homework~~

# Course reading for next class:~~ 12~~.~~1-12~~.~~3 (PDC)~~

# Assignment due by the start of Lecture #32: [[Attach:sp13.pdf|SP13]]

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].

# Course reading for next class

# Assignment due by the start of Lecture #32: [[Attach:sp13.pdf|SP13

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].

to:

!!!! Additional Material

* [[http://ctms.engin.umich.edu/CTMS/index.php?example=Introduction§ion=SystemModeling | Tutorial on Dynamic Modeling]]

* [[http://ctms.engin.umich.edu/CTMS/index.php?example=Introduction§ion=SystemModeling | Tutorial on Dynamic Modeling]]

Changed lines 3-4 from:

In this lecture we review the lab assignments and cover some information on converting a linearized model to state space form. ~~The model forms covered in this class include continuous and discrete state space and the Laplace domain. A brief tutorial on converting between these model forms in given in the video below:~~

to:

In this lecture we review the lab assignments and cover some information on converting a linearized model to state space form.

Changed line 9 from:

<iframe width="560" height="315" src="~~http:~~//www.youtube.com/embed/~~IGMGsSYLvMQ~~" frameborder="0" allowfullscreen></iframe>

to:

<iframe width="560" height="315" src="//www.youtube.com/embed/lGMGsSYLvMQ" frameborder="0" allowfullscreen></iframe>

Added lines 11-14:

!! MATLAB State Space and Transfer Function Models

The model forms covered in this class include continuous and discrete state space and the Laplace domain. A brief tutorial on converting between these model forms in given in the video below:

Changed line 9 from:

<iframe width="560" height="315" src="http://www.youtube.com/embed/~~ADPsPBxfwXE~~" frameborder="0" allowfullscreen></iframe>

to:

<iframe width="560" height="315" src="http://www.youtube.com/embed/IGMGsSYLvMQ" frameborder="0" allowfullscreen></iframe>

Changed line 6 from:

* %list list-page% [[Attach:cstr_example.zip | State Space Exercise Files (MATLAB)]]

to:

* %list list-page% [[Attach:cstr_example_files.zip | State Space Exercise Files (MATLAB)]]

Added lines 6-10:

* %list list-page% [[Attach:cstr_example.zip | State Space Exercise Files (MATLAB)]]

(:html:)

<iframe width="560" height="315" src="http://www.youtube.com/embed/ADPsPBxfwXE" frameborder="0" allowfullscreen></iframe>

(:htmlend:)

(:html:)

<iframe width="560" height="315" src="http://www.youtube.com/embed/ADPsPBxfwXE" frameborder="0" allowfullscreen></iframe>

(:htmlend:)

Added lines 4-5:

* %list list-page% [[Attach:Lecture31_handout2.pdf | State Space Exercise]]

Changed lines 14-33 from:

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].

to:

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].

----

(:html:)

<div id="disqus_thread"></div>

<script type="text/javascript">

/* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */

var disqus_shortname = 'apmonitor'; // required: replace example with your forum shortname

/* * * DON'T EDIT BELOW THIS LINE * * */

(function() {

var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;

dsq.src = 'http://' + disqus_shortname + '.disqus.com/embed.js';

(document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq);

})();

</script>

<noscript>Please enable JavaScript to view the <a href="http://disqus.com/?ref_noscript">comments powered by Disqus.</a></noscript>

<a href="http://disqus.com" class="dsq-brlink">comments powered by <span class="logo-disqus">Disqus</span></a>

(:htmlend:)

----

(:html:)

<div id="disqus_thread"></div>

<script type="text/javascript">

/* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */

var disqus_shortname = 'apmonitor'; // required: replace example with your forum shortname

/* * * DON'T EDIT BELOW THIS LINE * * */

(function() {

var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;

dsq.src = 'http://' + disqus_shortname + '.disqus.com/embed.js';

(document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq);

})();

</script>

<noscript>Please enable JavaScript to view the <a href="http://disqus.com/?ref_noscript">comments powered by Disqus.</a></noscript>

<a href="http://disqus.com" class="dsq-brlink">comments powered by <span class="logo-disqus">Disqus</span></a>

(:htmlend:)

Changed lines 1-7 from:

!!! Lecture 32 - ~~Model Predictive Control~~

Model Predictive Control (MPC) uses a mathematical representation of the process to predict and manipulate the future response of a system. ~~ Instead of a feedback strategy like PID control, MPC is actively making compensating moves to stay within constraints, drive to an economic optimum, and maximize or minimize certain quantities. Lecture 32 is an introduction to MPC and multivariable control.~~

* %list list-page% [[Attach:~~Lecture32_notes.pdf | Lecture 32 Notes]]~~

* %list list-page% [[Attach:~~Lecture32_handout.pdf | Lecture 32 Worksheet]]~~

Model Predictive Control (MPC) uses a mathematical representation of the process to predict and manipulate the future response of a system

* %list list-page% [[Attach

* %list list-page% [[Attach

to:

!!! Lecture 32 - State Space Modeling

In this lecture we review the lab assignments and cover some information on converting a linearized model to state space form. The model forms covered in this class include continuous and discrete state space and the Laplace domain. A brief tutorial on converting between these model forms in given in the video below:

(:html:)

<iframe width="560" height="315" src="http://www.youtube.com/embed/ADPsPBxfwXE" frameborder="0" allowfullscreen></iframe>

(:endhtml:)

In this lecture we review the lab assignments and cover some information on converting a linearized model to state space form. The model forms covered in this class include continuous and discrete state space and the Laplace domain. A brief tutorial on converting between these model forms in given in the video below:

(:html:)

<iframe width="560" height="315" src="http://www.youtube.com/embed/ADPsPBxfwXE" frameborder="0" allowfullscreen></iframe>

(:endhtml:)

Added lines 1-14:

!!! Lecture 32 - Model Predictive Control

Model Predictive Control (MPC) uses a mathematical representation of the process to predict and manipulate the future response of a system. Instead of a feedback strategy like PID control, MPC is actively making compensating moves to stay within constraints, drive to an economic optimum, and maximize or minimize certain quantities. Lecture 32 is an introduction to MPC and multivariable control.

* %list list-page% [[Attach:Lecture32_notes.pdf | Lecture 32 Notes]]

* %list list-page% [[Attach:Lecture32_handout.pdf | Lecture 32 Worksheet]]

!!!! Homework

# Course reading for next class: 12.1-12.3 (PDC)

# Assignment due by the start of Lecture #32: [[Attach:sp13.pdf|SP13]]

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].

Model Predictive Control (MPC) uses a mathematical representation of the process to predict and manipulate the future response of a system. Instead of a feedback strategy like PID control, MPC is actively making compensating moves to stay within constraints, drive to an economic optimum, and maximize or minimize certain quantities. Lecture 32 is an introduction to MPC and multivariable control.

* %list list-page% [[Attach:Lecture32_notes.pdf | Lecture 32 Notes]]

* %list list-page% [[Attach:Lecture32_handout.pdf | Lecture 32 Worksheet]]

!!!! Homework

# Course reading for next class: 12.1-12.3 (PDC)

# Assignment due by the start of Lecture #32: [[Attach:sp13.pdf|SP13]]

Relate each problem in the context of the [[Main/CourseCompetencies | overall course objectives]].