How to solve an equation system using a interp1-variable
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Hello everyone,
I'm trying to solve equations in a Matlab function that is part of a Simulink model.
One of those two equations is an interpolation of a given array.
% variable definiton
% T function argument
% p = f(T) values are given in form of a 69x2 double
% a | b | c | h constants / parameters (defined or calculated beforehand)
% equations
% eqn 1
% p = interp1(p(:,1),p(:,2),T)
% eqn 2
% h = a * T + p * (b + c * T)
% As I am used to solve equations with my pocket calculator I quickly found something like this while browsing:
syms T
solve (h == a * T + interp1(p(:,1),p(:,2),T) * (b + c * T),T);
% Unfortunately I do not have the required toolbox to solve equations which is why I need to find a work-around
% my next idea was to use an iteration to solve this (which I did not formulate and test until now)
% it would be something like that though:
for T = 1:100
p = interp1(p(:,1),p(:,2),T);
h_iter = a * T + p * (b + c * T);
if h_iter > h - h_marge | h_iter < h + h_marge
break
end
end
% with h_marge being a predefined value for accuracy tolerance
I would like to avoid such an iterational process since the iteration has to be done each simulation-step which could cause long simulation times
depending on the accuracy and the initial condition(s) I determine.
Thus, I wanted to ask you if there is another method / solution to solving that problem.
Look forward to hearing from you and thanks in advance.
Kind regards
Anton
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John D'Errico
2021 年 9 月 16 日
編集済み: John D'Errico
2021 年 9 月 16 日
interp1 is incompatible with symbolic parameters. You CANNOT use interp1 with solve. Period. So wherever you found that snippet of code, they were wrong.
You can use a tool like fzero with interp1. fzero and interp1 are compatible.
Next, looking at your problem, this is actually a TWO variable problem, with two equations. That is, we have known constants, a,b,c,h. And there are two unknowns. Sadly, you seem to be using p in two places at once, both as an array of known elements, and as a variable. And that is confusing as hell.
So I'll make the assumption that you have two variales, I'll call then T and p_T. That is p_T is given as:
p_T = interp1(p(:,1),p(:,2),T)
So, if I knew the value of T, then I could compute P_T. And then we have a second equation:
h = a * T + p_T * (b + c * T)
Now we can just substitute P_T in there. This reduces the problem to ONE equation, in one unknown, where you can use fzero. I've re-arranged it to be something you can see as a problem for fzero.
a * T + interp1(p(:,1),p(:,2),T) * (b + c * T) - h = 0
Now, given the variables a,b,c,h and the array p are defined as MATLAB variables in your workspace, set it up as:
fun = @(T) a * T + interp1(p(:,1),p(:,2),T) * (b + c * T) - h;
Tfinal = fzero(fun,[p(1,1),p(end,1)]);
That call will set a bracket on T, such that T must always lie between P(1,1) and P(69,1). That must make sense, since interp1 cannot intelligently evaluate its function beyond those limits anyway.
Again, a,b,c,h and p must all be previously defined in your workspace for that to work.
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