Simulink Apps Missing in Toolbar
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Hello All,
I am running into an issue with my simulink apps not showing up in the apps toolbar. The toolbart has some apps present, but the ones I need (Parameter Estimator, Simulink Test, etc) do not show up. The apps I need are within packages that I have already installed and have licenses and access to use. I am using an Enterprise licensing program through my job, if that helps at all. So far, I have ran the product installer multiple times, have tried adding them from the "Get Add-Ons" block (already installed so does not work), and have looked for help through the community but haven't had a solution yet. Thanks for any help.
回答 (2 件)
Andreas Goser
2024 年 11 月 5 日
編集済み: Andreas Goser
2024 年 11 月 7 日
Based on your description, I am under the impression you have tested good theories already what happens. If you have an enterprise license, your IT will be helpful and of course MathWorks support too. Here are a few thoughts:
- The "ver" command returns all installed products. They might not be licensed for you (on purpose or on error), the the product files are there
- To understand where the problem is, you could try an example and see if/what error message you get. Lets see Simulink Test https://www.mathworks.com/help/sltest/gs/create-a-simple-baseline-test.html. What do you get if you run the command?
open_system('sltestBasicCruiseControlBaseline')
7 件のコメント
Andreas Goser
2024 年 11 月 5 日
If you get a license error -> contact your IT
Andreas Goser
2024 年 11 月 8 日
OK, this is good. We can exclude this then. Let's look into the specifics. By the way, please share which release you are using and on which operating system. I use R2024a on Windows.
Simulink Test Manager opens with?
sltestmgr
If you open any model, go to the APPS tab, do you have Simulink Test available?
Ira
2024 年 11 月 8 日
I am using Release 2024b (I was using 2024a until about a month ago). I used the command you provided to open Simulink Test Manager, and I did recieve a license error for that, so I figure I will have to talk to IT about recieving access to Simulink Test. However I was able to run the model you sent in you previous comment with no issues.
These are the only apps in my apps toolbar (even when expanded).
The other app I need is the Parameter Estimator app. I know I have licenses to the Optimization Toolbox and the control system design toolboxes, but the app still does not show up.
I know I have licenses to the Optimization Toolbox and the control system design toolboxes, but the app still does not show up.
Can we check that you have those products installed in addition to being licensed?
To confirm that they're licensed, please show us the output of the ver function. You can edit out the license number when you post that output.
ver
To get a sense of what's installed, please show us the output of this command:
ls(fullfile(matlabroot, 'toolbox'))
Ira
2024 年 11 月 8 日
Andreas Goser
2024 年 11 月 11 日
Please point yout IT department to https://www.mathworks.com/matlabcentral/answers/98895-why-do-i-receive-license-manager-error-39
Prathiksha
2024 年 11 月 27 日
0 投票
clc;
clear;
close all;
% -----------------------
% PARAMETERS AND SIGNALS
% -----------------------
n_samples = 500; % Number of samples
t = 0:n_samples-1; % Time vector
% Desired signal (sinusoidal)
desired_signal = sin(2*pi*0.01*t);
% Additive white Gaussian noise (AWGN)
noise = 0.5 * randn(1, n_samples);
% Noisy signal
noisy_signal = desired_signal + noise;
% Channel variability simulation (fading)
fading = 0.5 + 0.5 * sin(2*pi*0.005*t); % Simulate channel gain variability
channel_signal = fading .* noisy_signal;
% -----------------------
% NOISE AND INTERFERENCE MITIGATION (LMS FILTERING)
% -----------------------
filter_order = 8; % Order of adaptive filter
mu = 0.01; % Learning rate for LMS
weights = zeros(filter_order, 1); % Initialize weights
filtered_signal = zeros(1, n_samples); % Initialize filtered signal
for i = filter_order:n_samples
x = noisy_signal(i:-1:i-filter_order+1); % Input vector
filtered_signal(i) = weights' * x'; % Filter output
error = desired_signal(i) - filtered_signal(i); % Error signal
weights = weights + 2 * mu * error * x'; % Update weights
end
% -----------------------
% ADAPTIVE MODULATION (BASED ON SNR)
% -----------------------
snr = 10 * log10(var(channel_signal) / var(noise)); % Compute SNR
if snr < 5
modulation_scheme = 'BPSK'; % Low SNR
elseif snr < 15
modulation_scheme = 'QPSK'; % Medium SNR
elseif snr < 25
modulation_scheme = '16-QAM'; % High SNR
else
modulation_scheme = '64-QAM'; % Very High SNR
end
disp(['Selected Modulation Scheme: ', modulation_scheme]);
% -----------------------
% SPECTRAL EFFICIENCY (OFDM)
% -----------------------
n_subcarriers = 64; % Number of OFDM subcarriers
modulation_order = 16; % 16-QAM
data = randi([0 modulation_order-1], n_subcarriers, n_samples); % Random data
% OFDM Modulation
modulated_data = qammod(data(:), modulation_order, 'UnitAveragePower', true);
ofdm_symbols = ifft(modulated_data, n_subcarriers);
% Adding AWGN to OFDM symbols
noisy_ofdm = awgn(ofdm_symbols, snr, 'measured');
% OFDM Demodulation
demodulated_data = fft(noisy_ofdm, n_subcarriers);
recovered_data = qamdemod(demodulated_data, modulation_order);
% -----------------------
% REAL-TIME ADAPTATION (KALMAN FILTER)
% -----------------------
x_estimated = zeros(1, n_samples); % Initialize estimated signal
P = 1; % Initial error covariance
Q = 0.01; % Process noise covariance
R = 0.5; % Measurement noise covariance
x = 0; % Initial state
for i = 1:n_samples
% Prediction step
P = P + Q; % Update error covariance
% Measurement update
K = P / (P + R); % Kalman gain
x = x + K * (noisy_signal(i) - x); % Update state estimate
P = (1 - K) * P; % Update error covariance
% Store the result
x_estimated(i) = x;
end
% -----------------------
% PLOT RESULTS
% -----------------------
figure;
% Original, Noisy, and Filtered signals
subplot(3, 1, 1);
plot(t, desired_signal, 'g', 'LineWidth', 1.5); hold on;
plot(t, noisy_signal, 'r', 'LineWidth', 1);
plot(t, filtered_signal, 'b', 'LineWidth', 1);
legend('Desired Signal', 'Noisy Signal', 'Filtered Signal');
title('LMS Filtering');
xlabel('Samples'); ylabel('Amplitude'); grid on;
% Fading channel effect
subplot(3, 1, 2);
plot(t, fading, 'k', 'LineWidth', 1.5);
title('Simulated Fading Channel');
xlabel('Samples'); ylabel('Channel Gain'); grid on;
% Kalman Filter adaptation
subplot(3, 1, 3);
plot(t, noisy_signal, 'r', 'LineWidth', 1); hold on;
plot(t, x_estimated, 'b', 'LineWidth', 1.5);
legend('Noisy Signal', 'Kalman Filter Output');
title('Kalman Filtering for Real-Time Adaptation');
xlabel('Samples'); ylabel('Amplitude'); grid on;
disp('Program completed successfully!');
what was wrong in this code
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