Hi @Ceferino
Please note that the input argument order for evalfis() has changed since the R2018b release. Additionally, there was a minor issue with the "ruleObjects," which I have fixed. I spent a few hours beautifying the final part of the plot in Figure 4 because I believe you intended to visualize both the Aggregated Output Membership Function and the Defuzzified crisp value.
I hope you like it!
PS. You will also notice that there is a slight discrepancy between the results returned by the evalfis() and the defuzz() commands.
% Create fuzzy input variables with triangular and trapezoidal membership functions
fis = mamfis;
% Add input variables
fis = addInput(fis, [0 100], "Name", "inputTemperature");
fis = addInput(fis, [0 100], "Name", "inputHumidity" );
% Add membership functions for input variables
fis = addMF(fis, "inputTemperature", 'trimf', [ 0 0 50], "Name", 'cold' );
fis = addMF(fis, "inputTemperature", 'trimf', [ 0 50 100], "Name", 'medium');
fis = addMF(fis, "inputTemperature", 'trimf', [50 100 100], "Name", 'hot' );
fis = addMF(fis, "inputHumidity", 'trimf', [ 0 0 50], "Name", 'low' );
fis = addMF(fis, "inputHumidity", 'trimf', [ 0 50 100], "Name", 'medium');
fis = addMF(fis, "inputHumidity", 'trimf', [50 100 100], "Name", 'high' );
figure(1)
subplot(211), plotmf(fis, 'input', 1), grid on
subplot(212), plotmf(fis, 'input', 2), grid on
% Add output variable
fis = addOutput(fis, [0 100], "Name", "heaterStrength");
% Add membership functions for the output variable
fis = addMF(fis, "heaterStrength", 'trimf', [ 0 0 25], "Name", "low" );
fis = addMF(fis, "heaterStrength", 'trimf', [25 50 75], "Name", "medium");
fis = addMF(fis, "heaterStrength", 'trimf', [50 75 100], "Name", "high" );
figure(2)
plotmf(fis, 'output', 1), grid on
% Define the fuzzy rules programmatically
rule1 = "IF inputTemperature IS cold AND inputHumidity IS high THEN heaterStrength IS high";
rule2 = "IF inputTemperature IS medium AND inputHumidity IS medium THEN heaterStrength IS medium";
rule3 = "IF inputTemperature IS hot AND inputHumidity IS low THEN heaterStrength IS low";
% Create a cell array of rules
Rules = [rule1, rule2, rule3];
% Convert the rule strings to rule objects
fis = addRule(fis, Rules);
showrule(fis)
% Display a high-level diagram of the Fuzzy Inference System (FIS)
figure(3)
% ruleview(fis)
plotfis(fis)
% Set input values
input_temperature = 35;
input_humidity = 70;
input_values = [input_temperature, input_humidity];
% Evaluate the fuzzy inference system
output = evalfis(fis, input_values);
% Print the input values and result
fprintf('Input Temperature: %f\n', input_temperature);
fprintf('Input Humidity: %f\n', input_humidity);
fprintf('Heater Strength: %f\n', output);
% Visualize the Defuzzification Result
xin1 = input_values(1);
xin2 = input_values(2);
in1mf1 = trimf(xin1, [ 0 0 50]); % temp cold
in1mf2 = trimf(xin1, [ 0 50 100]); % temp med
in1mf3 = trimf(xin1, [50 100 100]); % temp hot
in2mf1 = trimf(xin2, [ 0 0 50]); % humid low
in2mf2 = trimf(xin2, [ 0 50 100]); % humid med
in2mf3 = trimf(xin2, [50 100 100]); % humid high
fs1 = min(in1mf1, in2mf3) % Rule 1 firing strength
fs2 = min(in1mf2, in2mf2) % Rule 2 firing strength
fs3 = min(in1mf3, in2mf1) % Rule 3 firing strength
figure(4)
xout = 0:0.0001:100;
plotmf(fis, 'output', 1), ylim([-0.2 1.2]), hold on
pA1 = polyfit([25 50], [0 1], 1); % pA1(1)*x + pA1(2) = 0.6
pA2 = polyfit([50 75], [1 0], 1); % pA2(1)*x + pA2(2) = 0.6
AA = [pA1(1) 0; 0 pA2(1)];
Ab = [fs2-pA1(2); fs2-pA2(2)];
xA = linsolve(AA, Ab); % AA*xA = Ab
mfA = trapmf(xout, [25 xA(1) xA(2) 75]);
pB1 = polyfit([50 75], [0 1], 1); % pB1(1)*x + pB1(2) = 0.3
pB2 = polyfit([75 100], [1 0], 1); % pB2(1)*x + pB2(2) = 0.3
BA = [pB1(1) 0; 0 pB2(1)];
Bb = [fs1-pB1(2); fs1-pB2(2)];
xB = linsolve(BA, Bb); % BA*xB = Bb
mfB = trapmf(xout, [50 xB(1) xB(2) 100]);
aggomf = max(fs2*mfA, fs1*mfB);
plot(xout, aggomf, 'LineWidth', 3), grid on
xCentroid = defuzz(xout, aggomf, 'centroid')
hCentroid = line([xCentroid xCentroid], [-0.1 1.1], 'LineWidth', 2);
tCentroid = text(xCentroid, -0.1, ' centroid', 'FontWeight', 'bold');
yline(fs1, '--', 'fs1');
yline(fs2, '--', 'fs2');
h_gca = gca;
h_gca.YTick = [0.0 0.2 0.4 0.6 0.8 1.0];
% Create a text to point (xStart, yStart) and ending at (xFinal, yFinal)
x = [0.4 0.58]; % x-axis normalized figure coordinate [xStart, xFinal]
y = [0.7 0.50]; % y-axis normalized figure coordinate [yStart, yFinal]
txt = sprintf('heat str: %.3f ', xCentroid);
annotation('textarrow',x, y, 'String', txt)
