Can lqscurvefit() be used with mutiple independent X values?

I was trying to fit the model with multiple independent x values to find multiple parameters value. However, I could not fit the data myself with multiple independent X values. I was using the following code:

% Reading the dataframe
Follower=readtable('Follower.csv');
Leader = readtable('leader.csv');
Approx_fol=readtable('Approx_Fol');
Approx_lead=readtable('Approx_lead');

%finding the follower position
fol_pos = 482.768453-Approx_fol.fol_Smooth_Y;
% finding the leader position
pos_lead = 482.768453-Approx_lead.lead_Smooth_Y;

veh_len = 4.572;

%finding the gap
s = (pos_lead- fol_pos -veh_len)
Fol_v = Approx_fol.fol_Smooth_approx_v_vel;
lead_v = Approx_lead.lead_Smooth_approx_v_vel;

obj = zeros(521,1);
IDM_acc = zeros(521,1);
Velocity = zeros(521,1);
Position = zeros(521,1);
S_sim = zeros(521,1);

%Intial value of the parameters x0=[vo,T,so,a,b,delta]
%x0 = [15.8,1.41,3.4,2.35,1.9,4];
x0 = [20,1,3,2,2,4];
counter=1;
vo=x0(1);
T=x0(2);
so=x0(3);
a=x0(4);
b=x0(5);
delta=x0(6);

[S_sim] = IDM_Model(S_sim,x0(1),x0(2),x0(3),x0(4),x0(5),x0(6),obj,IDM_acc,Velocity,Position,Fol_v,fol_pos,lead_v,pos_lead,veh_len)

options = optimoptions('lsqcurvefit','Algorithm','levenberg-marquardt');

x = lsqcurvefit(IDM_Model,x0,obj,IDM_acc,Velocity,Position,Fol_v,fol_pos,lead_v,pos_lead,veh_len,s);

Here i m trying to find the parameter value of x0 using the levenberg-marquardt algorithm and trying to minimize the objective function (S_sim - s)^2 .

Any help in this regard would be appreaciated. Thanks in advance.

[Star Strider]

To do that, the independent variables must be put into a matrix, and referred to by the appropriate columns (since I prefer column-wise addressing in these instances).

So, if the model is —

with parameters a and b with independent variables p and q, define the independent variable array as —

pq = [p(:) q(:)];

and use it in the regression model as —

objfcn = @(b,x) exp(b(1).*x(:,1)) .* sin(b(2).*x(:,2)+b(3));

and go from there, defining ‘pq’ as the ‘x’ variable in the parameter estimation funcitons.

.

[Shashank Rajput]

Thanks, it worked fine!!!

[Star Strider]

My pleasure!

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