The ga function produces its best results if you override the default population matrix with one of your own. I always use an options structure similar to:
PopSz = 500;
Parms = 6;
opts = optimoptions('ga', 'PopulationSize',PopSz, 'InitialPopulationMatrix',randi(1E+4,PopSz,Parms)*1E-3, 'MaxGenerations',2E3, 'PlotFcn',@gaplotbestf, 'PlotInterval',1);
where ‘PopSz’ is the size (dimension 1) of the population matrix, and ‘Parms’ (dimension 2) is the number of parameters to optimise. It takes a bit longer, however it almost always converges successfully, if a solution exists. I use randi to more efficiently control the range of the random matrix.