MATLAB: Evaluating constants

constantsevaluation

Hello everyone,

I have to evaluate a very complicated number, and its important to me, so i can not use calculator to find because the accuracy will decrease, so I wrote the following code:

gm1 = 0.01; 
gm2 = 0.01;
gm4 = 0.04;
gm5 = 0.04;
gm7 = 0.04;
gm8 = 0.2;
re1 = 99;
re2 = 99;
re4 = 24.75;
re5 = 24.75;
re7 = 24.75;
re8 = 4.95;
ro1 = 400e3;
ro2 = 400e3;
ro4 = 100e3;
ro5 = 100e3;
ro8 = 20e3;
R1 = 20e3;
R2 = 20e3;
R3 = 3e3;
R4 = 2.3e3;
R5 = 15.7e3;
R6 = 3e3;
P1 = (R1*ro1)/(R1 + ro1);
P2 = (R2*ro2)/(R2 + ro2);
P3 = (R3*ro5)/(R3 + ro5);
P4 = (R6*ro8)/(R6 + ro8);
K1 = 101*(re8 + P4);
K2 = 101*(re7 + R4);
K3 = 101*(re5 + re4);
K4 = 101*(re1 + re2);
ANS2 = (P4/K4)*101*(100^3)*(R5/(R5+K1))*(P3/(P3+K2))*((P2+P1)/(P1+P2+K3));

as you can see, it is very complicated, now you can see that I will get the error " ??? Undefined function or variable" for all these constant.. so what should i do?

Best Answer

The posted code is working without an error. Matlab#s MLint mentions, that ro4 and all gm* variables are not used. But I do get an error message.

What about this:

ANS2 = 8010.837753694346;

Another impression: The accuracy of the output depends on the accuracy of the inputs. Did you analyse the sensitivity of the output to a variation of the inputs already? If accuracy matters, such an analysis is fundamental.

Related Solutions

MATLAB: When I run the program inaccurate results appear What is the problem

The best approach to this is likely not the vpasolve function, since it takes forever.

I have no idea of these are the ‘accurate’ results you want (I have no idea what that means), however you will get them much more quickly:

syms t y1 y2 y3 y4  yn11 yn1 yr yr11 yr111   yr v y(v) x
format longe
h=0.1;
r=1.7686999343761197980595002942562;   %1694/911=1.859495060373216e+00
x=0;
y0=0;
y01=0.25;
y011=0;
fn=-y01+y0.*y01.*y011;
fnr=-yr11+yr.*yr11.*yr111;
fn1=-yn1+y1.*yn1.*yn11;
fn2=-y3+y2.*y3.*y4;
eq1 =-y2-(r - 2)/r*y0+ 2/(r*(r - 1))*yr+ (2*r - 4)/(r - 1)*y1 -(h.^3.*(r^4 - 8*r^3 + 22*r^2 - 23*r + 6))/(120*r)*fn+ (h.^3.*(- r^2 + 2*r + 3))/(60*r)*fnr -(h.^3.*(- r^3 + 4*r^2 + 9*r - 26))/60*fn1+ (h.^3.*(- r^3 + 2*r + 1))/120*fn2;
eq1 = simplifyFraction(eq1);
eq1d = vpa(eq1, 5)
eq2= -h.*y3 -(r - 3)/r*y0+ 3/(r*(r - 1))*yr+ (r - 4)/(r - 1)*y1 -(h.^3.*(3*r^4 - 24*r^3 + 66*r^2 - 67*r + 12))/(240*r)*fn -(h.^3.*(r^4 - 5*r^3 + 5*r^2 + 5*r - 4))/(40*r*(r^2 - 3*r + 2))*fnr -(h.^3.*(- 3*r^4 + 15*r^3 + 15*r^2 - 137*r + 116))/(120*(r - 1))*fn1+ (h.^3.*(- r^4 + 2*r^3 + 2*r^2 + 3*r - 12))/(80*(r - 2))*fn2;
eq2 = simplifyFraction(eq2);
eq2d = vpa(eq2, 5)
eq3=-h.^2.*y4+2/r*y0+ 2/(r*(r - 1))*yr -2/(r - 1)*y1+ (h.^3.*(- r^4 + 8*r^3 - 22*r^2 + 18*r + 5))/(120*r)*fn -(h.^3.*(r^4 - 5*r^3 + 5*r^2 + 5*r + 5))/(60*r*(r^2 - 3*r + 2))*fnr -(h.^3.*(- r^4 + 5*r^3 + 5*r^2 - 75*r + 77))/(60*(r - 1))*fn1+ (h.^3.*(- r^4 + 2*r^3 + 2*r^2 + 42*r - 81))/(120*(r - 2))*fn2;
eq3 = simplifyFraction(eq3);
eq3d = vpa(eq3, 5)
eq4=-h.*yn1 -(r - 1)/r*y0+ 1/(r*(r - 1))*yr+ (r - 2)/(r - 1)*y1 -(h.^3.*(r^4 - 8*r^3 + 22*r^2 - 21*r + 6))/(240*r)*fn+ (h.^3.*(- r^2 + 2*r + 3))/(120*r)*fnr -(h.^3.*(- r^3 + 4*r^2 + 9*r - 8))/120*fn1 -(h.^3.*(r^3 - 2*r + 1))/240*fn2;
eq4 = simplifyFraction(eq4);
eq4d = vpa(eq4, 5)
eq5=-h.^2.*yn11+ 2/r*y0+ 2/(r*(r - 1))*yr -2/(r - 1)*y1 -(h.^3.*(r^4 - 8*r^3 + 22*r^2 - 28*r + 10))/(120*r)*fn -(h.^3.*(r^4 - 5*r^3 + 5*r^2 + 5*r - 10))/(60*r*(r^2 - 3*r + 2))*fnr -(h.^3.*(- r^4 + 5*r^3 + 5*r^2 - 35*r + 22))/(60*(r - 1))*fn1+ (h.^3.*(- r^4 + 2*r^3 + 2*r^2 - 8*r + 4))/(120*(r - 2))*fn2;
eq5 = simplifyFraction(eq5);
eq5d = vpa(eq5, 5)
eq6=-h.*yr11+ (r - 1)/r*y0+ (2*r - 1)/(r*(r - 1))*yr -r/(r - 1)*y1+ (h.^3.*(2*r^4 - 13*r^3 + 28*r^2 - 22*r + 5))/240*fn+ (h.^3.*(4*r^3 - 15*r^2 + 10*r + 5))/(120*(r - 2))*fnr+ (h.^3.*r*(- 2*r^3 + 7*r^2 + 2*r - 3))/120*fn1+ (h.^3.*r*(2*r^4 - 5*r^3 + 2*r^2 + 2*r - 1))/(240*(r - 2))*fn2;
eq6 = simplifyFraction(eq6);
eq6d = vpa(eq6, 5)
eq7=-h.^2.*yr111+ 2/r*y0+ 2/(r*(r - 1))*yr -2/(r - 1)*y1+ (h.^3.*(4*r^4 - 22*r^3 + 38*r^2 - 22*r + 5))/(120*r)*fn -(h.^3.*(- 14*r^4 + 55*r^3 - 55*r^2 + 5*r + 5))/(60*r*(r^2 - 3*r + 2))*fnr -(h.^3.*(4*r^4 - 15*r^3 + 5*r^2 + 5*r - 3))/(60*(r - 1))*fn1+ (h.^3.*(4*r^4 - 8*r^3 + 2*r^2 + 2*r - 1))/(120*(r - 2))*fn2;
eq7 = simplifyFraction(eq7);
eq7d = vpa(eq7, 5)
eq8=-h.*y01 -(r + 1)/r*y0 -1/(r*(r - 1))*yr+ r/(r - 1)*y1+ (h.^3.*(r^3 - 8*r^2 + 22*r - 5))/240*fn+ (h.^3.*(r^3 - 5*r^2 + 5*r + 5))/(120*(r^2 - 3*r + 2))*fnr+ (h.^3.*r*(- r^3 + 5*r^2 + 5*r - 3))/(120*(r - 1))*fn1 -(h.^3.*r*(- r^3 + 2*r^2 + 2*r - 1))/(240*(r - 2))*fn2;
eq8 = simplifyFraction(eq8);
eq8d = vpa(eq8, 5)
eq9 =-h.^2.*y011+ 2/r*y0+ 2/(r*(r - 1))*yr -2/(r - 1)*y1 -(h.^3.*(r^4 - 8*r^3 + 22*r^2 + 22*r - 5))/(120*r)*fn -(h.^3.*(r^4 - 5*r^3 + 5*r^2 + 5*r + 5))/(60*r*(r^2 - 3*r + 2))*fnr -(h.^3.*(- r^4 + 5*r^3 + 5*r^2 + 5*r - 3))/(60*(r - 1))*fn1+ (h.^3.*(- r^4 + 2*r^3 + 2*r^2 + 2*r - 1))/(120*(r - 2))*fn2;
eq9 = simplifyFraction(eq9);
eq9d = vpa(eq9, 5)
eqsfcn = matlabFunction([eq1,eq2,eq3,eq4,eq5,eq6,eq7,eq8,eq9], 'Vars',{[y1,y2,y3,y4,yn1,yn11,yr,yr11,yr111]})
eqsol = fsolve(eqsfcn, rand(1,9))
eqsolc = num2cell(eqsol);
[y1,y2,y3,y4,yn1,yn11,yr,yr11,yr111] = eqsolc{:}

I used the simplifyFraction function to do just that with your equations, then the fsolve function to do the actual calculations. These changes make it significantly more efficient.

The results I got are:

y1 =
     2.495835158216658e-02
y2 =
     4.966725033036157e-02
y3 =
     2.450145921764798e-01
y4 =
    -4.970810349993776e-02
yn1 =
     2.487509121241510e-01
yn11 =
    -2.496352514349295e-02
yr =
     4.398727143758653e-02
yr11 =
     2.460985502335340e-01
yr111 =
    -4.401564490668385e-02

You must be certain your equations are written as you want them to be in order to get ‘accurate’ values. We have no control over that.

Experiment to get the results you want.

MATLAB: Create X-axis limit

How about if you just add 5e-9 to all numbers:

close all
gm = 1e-6:1e-3:1;
grid on
hold on
%Rd = 1K
einv = 2.*sqrt((4e-9)^2+(4.*1.38e-23.*298.15.*1e3))
einv = einv./(gm*1e3) + 5e-9;
plot(gm,einv,'color',[0,0,0], 'LineWidth', 2);
%Rd = 10K
einv = 2.*sqrt((4e-9)^2+(4.*1.38e-23*298.15*10e3))
einv = einv./(gm*10e3) + 5e-9;
plot(gm,einv,'color',[0.25,0.25,0.25], 'LineWidth', 2);
%Rd = 100K
einv = 2.*sqrt((4e-9)^2+(4.*1.38e-23*298.15*100e3))
einv = einv./(gm*100e3) + 5e-9;
plot(gm,einv,'color',[0.5,0.5,0.5], 'LineWidth', 2);
%Rd = 1M
einv = 2.*sqrt((4e-9)^2+(4.*1.38e-23*298.15*1e6))
einv = einv./(gm*1e6) + 5e-9;
plot(gm,einv,'color',[0.75,0.75,0.75], 'LineWidth', 2);
xlabel ('gm (S)'); ylabel ( 'EINV_{min} (V/sqrt(Hz))');
set(gca,'xscale','log')
set(gca,'yscale','log')
legend('1K\Omega','10K\Omega','100K\Omega','1M\Omega');
%print('einv','-dpng')

Looks fairly good to me.

Best Answer

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MATLAB: When I run the program inaccurate results appear What is the problem

MATLAB: Create X-axis limit

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