MATLAB-如何定义多变量目标优化

时间:2018-10-16 02:09:37

标签: matlab optimization

我试图了解多变量目标优化,所以我需要优化复杂的功能,但是首先,我需要优化以下功能:

function ap_phase = objecfun(tau)

  f = 1000;   %Frequency

  w = 2*pi*f; %Angular Frequency

  trans_func = @(taux) (1-1i*w*taux)./(1+1i*w*taux); %Transfer function   

  trans_zero = trans_func(tau(1)); %Transfer function evaluated with the first variable
  trans_quad = trans_func(tau(2)); %Transfer function evaluated with the second variable

  ap_phase = rad2deg(phase(trans_zero)-phase(trans_quad)); %Phase difference

end

函数objecfun以一个长度为2的向量作为输入,计算2个传递函数,然后减去传递函数的相位。

我的目标是相位应在90°左右

以下是我用于优化的脚本

tau0 = [2E-5, 1E-3];        %Initial Value for tau(1) and tau(2)
lb = [1E-7, 1E-7];          %Lower bound for tau(1) and tau(2)
ub = [1E-2, 1E-2];          %Upper bound for tau(1) and tau(2)
goal = 90;                  %Optimization goal
weight = 1;                 %Weight
[x,fval] = fgoalattain(@objecfun,tau0,goal,weight,[],[],[],[],lb,ub)

优化器收敛,但是我得到了错误的答案,我得到了

x =

0.0100    0.0000

fval =

-178.1044

错了,fval应该在90°附近

我在做什么错了?

1 个答案:

答案 0 :(得分:1)

我认为您需要替换您的目标功能和目标值,以使其适合问题的表述。您可以将函数输出与所需角度之差的L2范数用作目标函数,并将目标设置为一定的公差。

我也检查了“ fmincon”:

new_goal = 1e-4;
objectfun = @(x) norm(objecfun(x) - goal);

options = optimoptions('fgoalattain');
options.PlotFcns = 'optimplotfval';
[tau_star,fval] = fgoalattain(objectfun,tau0,new_goal,weight,[],[],[],[],lb,ub,[],options);

options = optimoptions('fmincon');
options.PlotFcns = 'optimplotfval';
[tau_star2,fval,exitflag,output] = fmincon(objectfun,tau0,[],[],[],[],lb,ub,[], options);

fgoalattain_solution_phase_diff = objecfun(tau_star)
fmincon_solution_phase_diff = objecfun(tau_star2)

得到了:

fgoalattain_solution_phase_diff =

   90.0000


fmincon_solution_phase_diff =

   90.0006

注意:您还可以在函数中省略rad2deg并将其值[rad]用作所需的角度。