結果:

We introduced Difficulty Rating functionality during 2020 Cody Contest. Our Cody players have provided difficulty rating for most of the problems. Now we are displaying the ratings in the Problems list view.

Sorting and Filtering to follow...

Many educators use Simulink for their virtual labs. Starting in R2021a, you can add comments to blocks in a Simulink model. If you use Simulink in your class, you can use this to prompt questions to your students or to provide them feedback. Students working in groups can collaborate directly in the Simulink Editor, such as by suggesting alternative designs.

Click here to learn how to view, add, and reply to comments on blocks.

You may also want to learn more about Virtual Labs and Projects with MATLAB and Simulink, or read some Tips for Moving your Lab-based Classes Online.

Introducing content recommendations, a new feed on the community home page with personalized content just for you. MATLAB Central has hundreds of thousands of posts, including files, blogs, questions, and answers. We’re always looking for opportunities to better serve the community as it continues to grow so that visitors can easily help one another and ultimately find what they're looking for.

MATLAB Central has been around for a long time, 20 years this year - more on this milestone in a separate post later. With so much great content it can be a challenge to find what you're looking for or discover new things. We have search and browsing capabilities across the community but even with these robust features you still might not discover some very interesting or relevant content. In the spirit of trying to make sure you don't miss out, we've just released our first version of our recommended content feed. You can see this new feed on the community home page, visible by default via the 'For You' tab.

Recommendations are pulled from across MATLAB Central based on what we think would be relevant to you. We think we have a good starting point and plan on tweaking the algorithms now that it's live. So, expect the feed to only get more relevant over time.

We hope you will find this feature helpful and as always please reply with any feedback you may have.

New in R2021a, LimitsChangedFcn

LimitsChangedFcn is a callback function that responds to changes to axis limits ( release notes ). The function responds to axis interaction such as panning and zooming, programmatically setting the axis limits, or when axis limits are automatically adjusted by other processes.

LimitsChangedFcn is a property of ruler objects which are properties of axes and can be independently set for each axis. For example,

ax = gca(); 
ax.XAxis.LimitsChangedFcn = ... % Responds to changes to XLim
ax.YAxis.LimitsChangedFcn = ... % Responds to changes to YLim
ax.ZAxis.LimitsChangedFcn = ... % Responds to changes to ZLim

Previously, a listener could be assigned to respond to changes to axis limits. Here are some examples.

• Update refline when axis limits change
• Update axis2 limits when axis1 limits change

However, LimitsChangedFcn responds more reliably than a listener that responds to setting/getting axis limits. For example, after zooming or panning the axes in the demo below, the listener does not respond to the Restore View button in the axis toolbar but LimitsChangedFcn does! After restoring the view, try zooming out which does not result in changes to axis limits yet the listener will respond but the LimitsChangedFcn will not. Adding objects to axes after an axis-limit listener is set will not trigger the listener even if the added object expands the axis limits ( why not? ) but LimitsChangedFcn will!

ax = gca(); 
ax.UserData.Listener = addlistener(ax,'XLim','PostSet',@(~,~)disp('Listener')); 
ax.XAxis.LimitsChangedFcn = @(~,~)disp('LimitsChangedFcn')

How to use LimitsChangedFcn

The LimitsChangedFcn works like any other callback. For review,

• Callback Definition
• Write Callbacks for Apps

The first input to the LimitsChangedFcn callback function is the handle to the axis ruler object that was changed.

The second input is a structure that contains the old and new limits. For example,

    LimitsChanged with properties:

      OldLimits: [0 1]
      NewLimits: [0.25 0.75]
         Source: [1×1 NumericRuler]
      EventName: 'LimitsChanged'

Importantly, since LimitsChangedFcn is a property of the axis rulers rather than the axis object, changes to the axes may clear the LimitsChangedFcn property if the axes aren't held using hold on. For example,

% Axes not held
ax = gca(); 
ax.XAxis.LimitsChangedFcn = @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!'); 
plot(ax, 1:5, rand(1,5), 'o')
ax.XAxis.LimitsChangedFcn

ans =
    0×0 empty char array

% Axes held
ax = gca(); 
hold(ax,'on')
ax.XAxis.LimitsChangedFcn = @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!'); 
plot(ax, 1:5, rand(1,5), 'o')
ax.XAxis.LimitsChangedFcn

ans =
  function_handle with value:
    @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!')

Demo

In this simple app a LimitsChangedFcn callback function is assigned to the x and y axes. The function does two things:

1. Text boxes showing the current axis limits are updated
2. The prying eyes that are centered on the axes will move to the new axis center

This demo also uses Name=Value syntax and emoji text objects !

Create app

h.fig = uifigure(Name="LimitsChangedFcn Demo", ...
    Resize="off");
h.fig.Position(3:4) = [500,260];
movegui(h.fig)
h.ax = uiaxes(h.fig,...
    Units="pixels", ...
    Position=[200 26 250 208], ...
    Box="on");
grid(h.ax,"on")
title(h.ax,"I'm following you!")
h.eyeballs = text(h.ax, .5, .5, ...
    char([55357 56385 55357 56385]), ...
    HorizontalAlignment="center", ...
    FontSize=40);
h.label = uilabel(h.fig, ...
    Text="Axis limits", ...
    Position=[25 212 160 15], ...
    FontWeight="bold",...
    HorizontalAlignment="center");
h.xtxt = uitextarea(h.fig, ...
    position=[25 191 160 20], ...
    HorizontalAlignment="center", ...
    WordWrap="off", ...
    Editable="off",...
    FontName=get(groot, 'FixedWidthFontName'));
h.ytxt = uitextarea(h.fig, ...
    position=[25 165 160 20], ...
    HorizontalAlignment="center", ...
    WordWrap="off", ...
    Editable="off", ...
    FontName=get(groot, 'FixedWidthFontName'));
h.label = uilabel(h.fig, ...
    Text=['X',newline,newline,'Y'], ...
    Position=[10 170 15 38], ...
    FontWeight="bold");

Set LimitsChangedFcn of x and y axes

h.ax.XAxis.LimitsChangedFcn = @(hObj,data)limitsChangedCallbackFcn(hObj,data,h,'x');
h.ax.YAxis.LimitsChangedFcn = @(hObj,data)limitsChangedCallbackFcn(hObj,data,h,'y');

Update text fields

xlim(h.ax, [-100,100])
ylim(h.ax, [-100,100])

Define LimitsChangedFcn

function limitsChangedCallbackFcn(rulerHand, limChgData, handles, xy)
% limitsChangedCallbackFcn() responds to changes to x or y axis limits.
% - rulerHand: Ruler handle for x or y axis that was changed (not used in this demo)
% - limChgData: LimitsChanged data structure
% - handles: structure of App handles
% - xy: either 'x' or 'y' identifying rulerHand
switch lower(xy)
    case 'x'
        textHandle = handles.xtxt;
        positionIndex = 1; 
    case 'y'
        textHandle = handles.ytxt;
        positionIndex = 2; 
    otherwise
        error('xy is a character ''x'' or ''y''.')
end
% Update text boxes showing rounded axis limits
textHandle.Value = sprintf('[%.3f, %.3f]',limChgData.NewLimits);
% Move the eyes to the new center position
handles.eyeballs.Position(positionIndex) = limChgData.NewLimits(1)+range(limChgData.NewLimits)/2; % for linear scales only!
drawnow
end

See attached mlx file for a copy of this thread.

Highlight Icon image

We will be hosting a seminar on MATLAB Grader, the product I manage at MathWorks, on April 21st at 7am EDT. If you are interested in adding autograding capabilities for #MATLAB to your course, MOOC, textbook, or learning environment and have questions, please join this seminar and take part in the live Q&A with the product team the following week. #autograding #assessments #onlineassessment #onlineteaching

MathWorks Seminar: Autograded Assessments with MATLAB Grader & LMS Integration

hi everyone could you explain to me why the three phase voltages in this video are not sinusoïdale and how to change them To be sinusoidale?

Youtube video: Motor Control Design with MATLAB and Simulink

link:https://www.youtube.com/watchv=lP4jbmthiyc&t=1103s&ab_channel=MATLAB

We are introducing Scratch Pad in Cody to support iterative problem solving. Scratch Pad will enable you to build your solution line-by-line, experiment with different MATLAB functions, and test your solution before submitting.

Try it out and let us know what you think.

why does this work?

Starting in MATLAB R2021a, name-value arguments have a new optional syntax!

A property name can be paired with its value by an equal sign and the property name is not enclosed in quotes.

Compare the comma-separated name,value syntax to the new equal-sign syntax, either of which can be used in >=r2021a:

• plot(x, y, "b-", "LineWidth", 2)
• plot(x, y, "b-", LineWidth=2)

It comes with some limitations:

1. It's recommended to use only one syntax in a function call but if you're feeling rebellious and want to mix the syntaxes, all of the name=value arguments must appear after the comma-separated name,value arguments.
2. Like the comma-separated name,value arguments, the name=value arguments must appear after positional arguments.
3. Name=value pairs must be used directly in function calls and cannot be wrapped in cell arrays or additional parentheses.

Some other notes:

1. The property names are not case-sensitive so color='r' and Color='r' are both supported.
2. Partial name matches are also supported. plot(1:5, LineW=4)

The new syntax is helpful in distinguishing property names from property values in long lists of name-value arguments within the same line.

For example, compare the following 2 lines:

h = uicontrol(hfig, "Style", "checkbox", "String", "Long", "Units", "Normalize", "Tag", "chkBox1")

h = uicontrol(hfig,  Style="checkbox",    String="Long",    Units="Normalize",    Tag="chkBox1")

Here's another side-by-side comparison of the two syntaxes. See the attached mlx file for the full code and all content of this Community Highlight.

tiledlayout, introduced in MATLAB R2019b, offers a flexible way to add subplots, or tiles, to a figure.

Reviewing two changes to tiledlayout in MATLAB R2021a

1. The new TileIndexing property
2. Changes to TileSpacing and Padding properties

1) TileIndexing

By default, axes within a tiled layout are created from left to right, top to bottom, but sometimes it's better to organize plots column-wise from top to bottom and then left to right. Starting in r2021a, the TileIndexing property of tiledlayout specifies the direction of flow when adding new tiles.

tiledlayout(__,'TileIndexing','rowmajor') creates tiles by row (default).

tiledlayout(__,'TileIndexing','columnmajor') creates tiles by column.

.

2) TileSpacing & Padding changes

Some changes have been made to the spacing properties of tiles created by tiledlayout.

TileSpacing: sets the spacing between tiles.

• "loose" is the new default and replaces "normal" which is no longer recommended but is still accepted.
• "tight" replaces "none" and brings the tiles closer together still leaving space for axis ticks and labels.
• "none" results in tile borders touching, following the true meaning of none.
• "compact" is unchanged and has slightly more space between tiles than "tight".

Padding: sets the spacing of the figure margins.

• "loose" is the new default and replaces "normal" which is no longer recommended but is still accepted.
• "tight" replaces "none" and reduces the figure margins. "none" is no longer recommended but is still accepted.
• "compact" is unchanged and adds slightly more marginal space than "tight".
• Reducing the figure margins to a true none is still not an option.

The release notes show a comparison of these properties between r2020b and r2021a.

Here's what the new TileSpacing options (left column of figures below) and Padding options (right column) look like in R2021a. Spacing properties are written in the figure names.

.

And here's a grid of all 12 combinations of the 4 TileSpacing options and 3 Padding options in R2021a.

.

Code used to generate these figures

%% Animate the RowMajor and ColumnMajor indexing with colored tiles 
fig1 = figure('position',[200 200 560 420]); 
tlo1 = tiledlayout(fig1, 3, 3, 'TileIndexing','rowmajor');
title(tlo1, 'RowMajor indexing')

fig2 = figure('position',[760 200 560 420]); 
tlo2 = tiledlayout(fig2, 3, 3, 'TileIndexing','columnmajor');
title(tlo2, 'ColumnMajor indexing')

colors = jet(9);
drawnow()

for i = 1:9
    ax = nexttile(tlo1);
    ax.Color = colors(i,:);
    text(ax, .5, .5, num2str(i), 'Horiz','Cent','Vert','Mid','Fontsize',24)

      ax = nexttile(tlo2);
      ax.Color = colors(i,:);
      text(ax, .5, .5, num2str(i), 'Horiz','Cent','Vert','Mid','Fontsize',24)

      drawnow
      pause(.3)
  end

%% Show TileSpacing options
tileSpacing = ["loose","compact","tight","none"];
figHeight = 140;  % unit: pixels
figPosY = fliplr(50 : figHeight+32 : (figHeight+30)*numel(tileSpacing)); 

for i = 1:numel(tileSpacing)
    uif = uifigure('Units','Pixels','Position', [150 figPosY(i) 580 figHeight], ...
        'Name', ['TileSpacing: ', tileSpacing{i}]);
    tlo = tiledlayout(uif,1,3,'TileSpacing',tileSpacing(i)); 
    h = arrayfun(@(i)nexttile(tlo), 1:tlo.GridSize(2));
    box(h,'on')
    drawnow()
end

%% Show Padding options
padding = ["loose","compact","tight"];
for i = 1:numel(padding)
    uif = uifigure('Units','Pixels','Position', [732 figPosY(i) 580 figHeight], ...
        'Name', ['Padding: ', padding{i}]);
    tlo = tiledlayout(uif,1,3,'Padding',padding(i)); 
    h = arrayfun(@(i)nexttile(tlo), 1:tlo.GridSize(2));
    box(h,'on')
    drawnow()
end

%% Show all combinations of TileSpacing and Padding options
tileSpacing = ["loose","compact","tight","none"];
padding = ["loose","compact","tight"];
[tsIdx, padIdx] = meshgrid(1:numel(tileSpacing), 1:numel(padding));
figSize = [320 220]; % width, height (pixels)
figPosX = 150 + (figSize(1)+2)*(0:numel(tileSpacing)-1); 
figPosY = 50 + (figSize(2)+32)*(0:numel(padding)-1);
[figX, figY] = meshgrid(figPosX, fliplr(figPosY));
for i = 1:numel(padIdx)
    uif = uifigure('Units','pixels','Position',[figX(i), figY(i), figSize], ...
        'name', ['TS: ', tileSpacing{tsIdx(i)}, ', Pad: ', padding{padIdx(i)}]);
    tlo = tiledlayout(uif,2,2,'TileSpacing',tileSpacing(tsIdx(i)),'Padding',padding(padIdx(i))); 
    h = arrayfun(@(i)nexttile(tlo), 1:prod(tlo.GridSize));
    box(h,'on')
    drawnow()
end

let me invite you to distant Second international conference "MATLAB and computer calculations in education, science and engineering" April 26 – 29, 2021 р., Kyiv"

First communication

It is impossible to imagine recent science and engineering without mathematical packages like MATLAB, MathCAD, Mathematica, Maple etc. However, they have not been sufficiently used in education yet. To improve the situation we manage these conferences. This will be the Second conference in Ukraine. The First was carried out in May 2019. Its results may be seen here. Unfortunately, it should be carried out remotely this time. However, it is to happen to have the tradition saved!

Scientists, engineers, educators from universities and high schools are welcome! Regretfully, we need to restrict the scope of topics to be considered this time. They are to be associated with education in university or school, methodology of mathematical package application, teaching disciplines with them. Variety of problems we see in such a way this time:

Problems and sections:  MATLAB and computer use in universities  MATLAB and computer use and computer use in high school

Conference will be held remotely under supervision of National aviation university (Kyiv). Like last time, (remote) master classes will be carried out to, from our point, to facilitate MATLAB use for beginners in education. To facilitate remote participation of foreign guests, two kinds of sessions will be managed: Morning sections, 10 a.m. – 15 p.m. Kyiv’ time will use Ukrainian and Russian languages. Evening sections, 18 p.m. -:- 21 p.m. Kyiv’ time but 10 a.m. – 1 p.m. in San Francisco will use English, for participants from Europe and USA.

Organizational Committee and rules for Abstracts may be seen here, or in department site or asked for per e-mail Ye_Gayev@i.ua and YevgenyAlGayev@gmail.com

Important dates Till April 10, 2021 – registration via form or directly via above addresses. Till April 20, 2021 р. – accepting Abstracts, 4 pages prepared on rules. Opening the conference April 26, 2021. Conference days 26 – 28, April 2021. Book of Abstracts will be placed in the Internet and in https://www.academia.edu/; DOI will supplement them.

It is important that three master-classes are to be carried out in Saturday and Sunday, April 24 and 25. Their topics are:

1. Prof. Yevgeny Gayev (NAU) «Algorithms that inspire to education»; 2. Prof. Sergii Iglin (Kharkov) «Heat Transfer problems with MATLAB»; 3. Prof. Sergey Sylantyev (Kyiv Nat. univ.) «AWS Cloud Services and Cloud Calculation».

Potential participants are kindly asked to register as soon as possible for enabling our next management steps!

Did you know you can use most emoticons in text objects?

Most emoticons are just unicode characters. Using them as characters in Matlab is as simple as finding their numeric representation and then converting the numeric value back to character. Not all emoticons are convertible in Matlab.

Here's a secret message with emoticons. Use char(x) to decode it.

x = [79 77 71 33 32 55357 56878 32 104 97 118 101 32 121 111 ...
    117 32 117 112 100 97 116 101 100 32 116 111 32 77 97 116 ...
    108 97 98 32 55358 56595 32 114 50 48 50 49 97 32 121 101 116 32 8265];

Happy St. Patrick's Day!

fig = figure('MenuBar','none','Color', [0 .62 .376]);  % Shamrock green
ax = axes(fig,'Units','Normalized','Position',[0 0 1 1]);
axis(ax,'off')
axis(ax,'equal')
hold(ax,'on')
xlim(ax,[-1,1]); ylim(ax,[-1,1])
text(ax, 0, 0, char(9752), 'VerticalAlignment','middle','HorizontalAlignment','center','FontSize', 200)
str = num2cell('Happy St Patrick''s day!');
th = linspace(-pi/2,pi/2,numel(str)); 
txtHandle = text(ax,sin(th)*.8, cos(th)*.8, str, 'VerticalAlignment','middle','HorizontalAlignment','center','FontSize', 25);
set(txtHandle,{'rotation'}, num2cell(rad2deg(-th')))
thr = 0.017;
rotateCCW = @(xyz)([cos(thr) -sin(thr) 0; sin(thr), cos(thr), 0; 0 0 1]*xyz.').';
while all(isvalid(txtHandle))
    newposition = rotateCCW(vertcat(txtHandle.Position)); 
    set(txtHandle,{'position'}, mat2cell(newposition,ones(numel(txtHandle),1),3), ...
        {'rotation'}, num2cell([txtHandle.Rotation].'+thr*180/pi))
    drawnow()
end

We've all been there. You've got some kind of output that displays perfectly in the command window and you just want to capture that display as a string so you can use it again somewhere else. Maybe it's a multidimensional array, a table, a structure, or a fit object that perfectly displays the information you need in a neat and tidy format but when you try to recreate the display in a string variable it's like reconstructing the Taj Mahal out of legos.

Enter Matlab r2021a > formattedDisplayText()

Use str=formattedDisplayText(var) the same way you use disp(var) except instead of displaying the output, it's stored as a string as it would appear in the command window.

Additional name-value pairs allow you to

• Specify a numeric format
• Specify loose|compact line spacing
• Display true|false instead of 1|0 for logical values
• Include or suppress markup formatting that may appear in the display such as the bold headers in tables.

Demo: Record the input table and results of a polynomial curve fit

load census
[fitobj, gof] = fit(cdate, pop, 'poly3', 'normalize', 'on')

Results printed to the command window:

fitobj = 
     Linear model Poly3:
     fitobj(x) = p1*x^3 + p2*x^2 + p3*x + p4
       where x is normalized by mean 1890 and std 62.05
     Coefficients (with 95% confidence bounds):
       p1 =       0.921  (-0.9743, 2.816)
       p2 =       25.18  (23.57, 26.79)
       p3 =       73.86  (70.33, 77.39)
       p4 =       61.74  (59.69, 63.8)

gof = 
  struct with fields:

             sse: 149.77
         rsquare: 0.99879
             dfe: 17
      adjrsquare: 0.99857
            rmse: 2.9682

Capture the input table, the printed fit object, and goodness-of-fit structure as strings:

rawDataStr = formattedDisplayText(table(cdate,pop),'SuppressMarkup',true)
fitStr = formattedDisplayText(fitobj)
gofStr = formattedDisplayText(gof)

Display the strings:

rawDataStr = 
    "    cdate     pop 
         _____    _____
         1790       3.9
         1800       5.3
         1810       7.2
         1820       9.6
         1830      12.9
         1840      17.1
         1850      23.1
         1860      31.4
         1870      38.6
         1880      50.2
         1890      62.9
         1900        76
         1910        92
         1920     105.7
         1930     122.8
         1940     131.7
         1950     150.7
         1960       179
         1970       205
         1980     226.5
         1990     248.7
     "

fitStr = 
    "     Linear model Poly3:
          ary(x) = p1*x^3 + p2*x^2 + p3*x + p4
            where x is normalized by mean 1890 and std 62.05
          Coefficients (with 95% confidence bounds):
            p1 =       0.921  (-0.9743, 2.816)
            p2 =       25.18  (23.57, 26.79)
            p3 =       73.86  (70.33, 77.39)
            p4 =       61.74  (59.69, 63.8)
     "

gofStr = 
    "           sse: 149.77
            rsquare: 0.99879
                dfe: 17
         adjrsquare: 0.99857
               rmse: 2.9682
     "

Combine the strings into a single string and write it to a text file in your temp directory:

txt =  strjoin([rawDataStr; fitStr; gofStr],[newline newline]);
file = fullfile(tempdir,'results.txt');
fid = fopen(file,'w+');
cleanup = onCleanup(@()fclose(fid)); 
fprintf(fid, '%s', txt);
clear cleanup

Open results.txt.

winopen(file) % for Windows platforms

Hi All,

Quick question regarding deriving PM flux linkage [Wb] from a torque constant estimated from data on a PMLSM.

I have an estimated torque constant Kt [N/A], which is from experimental test data. I will now parameterising my Simscape PMLSM block from this torque constant.

The literature seems confusing, to derive PM flux linkage [Wb] from the experimental torque contant do i include the (3/2) constant. Some examples include the constant and some omit, which one of the following is preferred for deriving the PM flux linkage?

Thanks

Patrick

Hi, MathWorks / MATLAB / Simulink community! I have recently started working my way through the book mentioned in the topic, and I am wondering if anybody out there would be interested and have time to help me review some of my work on the exercises. Specifically, I'm currently working "Exercise 7.9 - Challenge: Design of a Type 2 PLL" and I am not convinced that my implementation is correct, but I'm having some trouble with debugging.

Is anyone interested and have time to review my implementation and give some feedback? I'd definitely appreciate it.

Thanks!

Shaun Lippy Middleburg, VA, USA

ASME will be hosting a four-part conversation series from March 22-25, that will educate and equip mechanical engineers with workforce strategies. The series will bring together leaders and industry experts in education to explore which new skills will be taught to young engineers, what training mid-career engineers need in order to return to work as the pandemic subsides, and how much more can be done to confront the labor and skills gap in 2021 and beyond.

I was honored to be asked to participate in the first panel discussion along with distinguished faculty from MIT and the University of Colorado Boulder. I would encourage all of our customers involved in online teaching and learning to attend. More details on the panel discussion that features MathWorks response to COVID-19 are below:

The Evolution of Engineering Education Post-COVID-19 (March 22): The transition to remote learning was a shock for many universities and colleges across the country. Professors had to transform their in-person lecture into an engaging online class, and students had to take on more self-learning responsibilities. What impact will this change in teaching have on the future of education? This conversation will focus on the shift to online education at universities, the digital engineering skills students will need to learn, and how academia and industry can work together to prepare the young engineers entering the workforce.

The Evolution of Engineering Education Post-COVID-19 : https://app.webinar.net/vlOW9kK90wm?mcc=EDIT

I just started my MPhil in power systems and we are doing load flow analysis. I am completely lost throughout the gauss seidel and newton Raphson methods using MatLab. can I get help, please?

This is a great presentation from 2 professors introducing how they use MATLAB in their physics courses. MATLAB Grader and Live Scripts are discussed in detail.

YouTube Video

Here is the abstract:

-----

Guest Presenters: Michele McColgan, Siena College and Duncan Carlsmith, UW Madison

The meeting will start with short presentations, and then we'll have time for questions and discussion in a colloquial setting. The presenters use MATLAB in their courses, and this meeting will provide a good opportunity to see the functionality that MATLAB affords. However, the presenters' approach to integrating computation is relevant generally; thus, this meeting should be of great interest, even if you are not a MATLAB user.

-----

Webinar from PICUP .

Prof. Duarte Antunes from Eindhoven University of Technology explains how he's been using MATLAB live scripts for teaching an online "Optimal Control and Dynamic Programming" course.

https://www.mathworks.com/company/newsletters/articles/using-matlab-live-scripts-to-teach-optimal-control-and-dynamic-programming-online.html