How to write Fmincon when I have two "to be optimized variables"?

I have two variables which I'm going to use Fmincon to optimize. Both of the variables are changing with time. I write Fmincon as below:

% Simulation time

Time = 0:0.005:25; 

% Initial Guess for the control input at every time interval

TopS_FL0 = 0.2 .* ones(length(Time),1);

TopS_RL0 = 0.2 .* ones(length(Time),1);

% Bounds for control input at every time interval

TopS_FL_L = 0 .* ones(length(Time),1);

TopS_FL_U = 1 .* ones(length(Time),1);

TopS_RL_L = 0 .* ones(length(Time),1);

TopS_RL_U = 1 .* ones(length(Time),1);

[ Topt1, Topt2 ] = fmincon( @( Top_FL, Top_RL )obj( other parameters_1, Top_FL, Top_RL), [TopS_FL0, TopS_RL0], [], [], [], [], [TopS_FL_L, TopS_RL_L],[TopS_FL_U, TopS_RL_U],...
@( Top_FL, Top_RL )ctr( other parameters_2, Top_FL, Top_RL ), optNLP);

When I run my code, it always shows that:

Not enough input arguments.

Error in fmincon (line 534)
      initVals.f = feval(funfcn{3},X,varargin{:});

Caused by:
    Failure in initial user-supplied objective function evaluation. FMINCON cannot continue.

Can anyone give me some help? Thank you very much.

Answer 1

[Alan Weiss]

As the documentation clearly states, fmincon expects your objective function to accept a vector of input variables, and output a scalar. So you need to do something like

 fun = @(x)obj(x,other_parameters)

where fun is something like

 function y = obj(x,other_parameters)
 Top_FL = x(1);
 Top_RL = x(2)
 ...

Alan Weiss

MATLAB mathematical toolbox documentation

[Tao]

Thank you very much!

[Yaser Khojah]

Dear Alan,

I have an optimization problem where my function has two control variables as the following

 function [NetPV,finalSupply] = OptimizedRate (Weights,NRates)

Weights and NRates are vectors as: Weights = [x1 x2 x3] and NRates = [y1 y2 y3]

I want to optimized Weights and NRates not just passing one of them. I have seen some examples like: https://uk.mathworks.com/help/optim/ug/passing-extra-parameters.html

and tried them. However this pass NRates variable instead of optimizing it.

[x,fval,exitflag,output] = patternsearch(@(Weights)OptimizedRate(Weights,NRates),x0,[],[],Aeq,beq,LB,UB,options);

I'm looking for away to optimize Weights and NRates variables jointly.

Thanks for your help!

[Walter Roberson]

initial_weights = rand(1,3);    %use something more meaningful
initial_nrates = rand(1,3);     %use something more meaningful
x0 = [initial_weights, initial_nrates];
[x,fval,exitflag,output] = patternsearch( @OptimizedRate, x0, [], [], Aeq, beq, LB, UB, options);

with

function f = OptimizedRate(x)
  Weights = x(1:3);
  NRates = x(4:6);
  ...

[Yaser Khojah]

Thanks Walter. How would you write the linear constraint in this case?

[Walter Roberson]

Example:

A = [1 1 -2 0 0 0;
     0 0  0 0 1 -1]
b = [0;
     0]

to express Weights(1) + Weights(2) <= 2 * Weights(3) & Nrates(2) <= Nrates(3)