One proper way to plot the membership functions (MFs) is to create custom MFs based on the given fuzzy sets.
Since this is not possible to save customMF.m online, the Logistic function (aka Sigmoidal MF) from the toolbox can be used to approximate the fuzzy sets.
% Data Sets
u = (0:9)';
A = [0.0 0.0 0.1 0.2 0.3 0.8 0.9 1.0 1.0 1.0]';
B = [1.0 1.0 0.9 0.8 0.7 0.5 0.4 0.2 0.2 0.0]';
% Curve-fitting
fo = fitoptions('Method','NonlinearLeastSquares',...
'Lower',[-10, -10],...
'Upper',[ 10, 10],...
'StartPoint', [1 1]);
ft = fittype('1/(1 + exp(-a*(x - c)))', 'options', fo);
[sigmA, gof] = fit(u, A, ft)
[sigmB, gof] = fit(u, B, ft)
figure(1)
plot(u, A, '.'), hold on
plot(sigmA, 'r'), hold off
grid on, xlabel('u'), ylabel('A(u)')
legend('Set A', 'Fitted Sigmoid', 'location', 'best')
figure(2)
plot(u, B, '.'), hold on
plot(sigmB, 'r'), hold off
grid on, xlabel('u'), ylabel('B(u)')
legend('Set B', 'Fitted Sigmoid', 'location', 'best')
% Creating FIS and putting the input MFs into FIS
fis = mamfis('Name', "user_FIS");
% Fuzzy Input
fis = addInput(fis, [0 9], 'Name', 'U');
fis = addMF(fis, 'U', 'sigmf', [sigmB.a sigmB.c], 'Name', 'LO');
fis = addMF(fis, 'U', 'sigmf', [sigmA.a sigmA.c], 'Name', 'HI');
% Plot membership functions
figure(3)
plotmf(fis, 'input', 1), grid on, title('U')
