Solving for a matrix

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hrushikesh kyathari
hrushikesh kyathari on 4 Aug 2019
Answered: John D'Errico on 4 Aug 2019
C is a variable matrix, C=[w,x,y,x]
I have an equation T*Q*M=B; All the matrices are 4*4
B and Q are known constant matrices. But T and M are matrices which have elements as a function of variables in C.
For example: T=[0,cos(x).sin(y),0,
0,0,0,0,
1,1,1,1
0,0,0,0]
Similarly M.
Is it possible to solve for the matrix C(i.e for the variables in C).Help if possible
  5 Comments
hrushikesh kyathari
hrushikesh kyathari on 4 Aug 2019
Tsb=[cos(c(1,1)),-sin(c(1,1)),0,c(2,1),
sin(c(1,1)),cos(c(1,1)),0,c(3,1),
0,0,1,0.0963,
0,0,0,1];
Tbo=[1,0,0,0.1662,
0,1,0,0,
0,0,1,0.0026
0,0,0,1];
M=[1,0,0,0.033,
0,1,0,0,
0,0,1,0.6546,
0,0,0,1];
Slist=[0,0,1,0,0.033,0,
0,-1,0,-0.5076,0,0,
0,-1,0,-0.3526,0,0,
0,-1,0,-0.2176,0,0,
0,0,1,0,0,0]';
Toe=FKinBody(M,Slist,c((4:8),1));
fun=(Tsb*Tbo*Toe)-X;
H = fsolve(fun,-500)
This is my code, When I try to run Fsolve it is showing error:FUN must be a function, a valid character vector expression, or an inline function object.
Walter Roberson
Walter Roberson on 4 Aug 2019
Edited: Walter Roberson on 4 Aug 2019
What is FKinBody ?
In
fun=(Tsb*Tbo*Toe)-X;
what is X ? And what happened to B ?

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Answers (2)

Walter Roberson
Walter Roberson on 4 Aug 2019
Tsb = @(c) [cos(c(1)), -sin(c(1)), 0, c(2);
sin(c(1)), cos(c(1)), 0, c(3);
0, 0, 1, 0.0963;
0, 0, 0, 1];
Tbo=[1, 0, 0, 0.1662;
0, 1, 0, 0;
0, 0, 1, 0.0026;
0, 0, 0, 1];
M=[1, 0, 0, 0.033;
0, 1, 0, 0;
0, 0, 1, 0.6546;
0, 0, 0, 1];
Slist=[0, 0, 1, 0, 0.033, 0;
0, -1, 0, -0.5076, 0, 0;
0, -1, 0, -0.3526, 0, 0;
0, -1, 0, -0.2176, 0, 0;
0, 0, 1, 0, 0, 0]';
Toe = @(c) FKinBody(M, Slist, c(4:8));
fun = @(c) (Tsb(c) * Tbo * Toe(c)) - B;
c0 = randi([-1000 1000], 1, 4);
H = fsolve(fun, c0)

John D'Errico
John D'Errico on 4 Aug 2019
You have what? 2 unknowns? I've seen various versions of these equations that you have written. But you do not have 16 unknowns.
You want 16 equations to be solved. That 4x4 matrix equation is equivalent to 16 equations. So unless you have 16 unknowns, you need to accept the solution will not be exact.
So you will use a solver that will handle a nonlinear least squares. I might suggest something like lsqnonlin or lsqcurvefit. They are not just there for curve fitting.

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