I am new here and I am not used to the Kalman theory and algorithm implementation. I need some help with the Kalman algorithm implementation. I need to control a process where the measure can be affected by drift. I believe that Kalman could be the solution for this. But I do not know how to do.

Let's suppose I need to control the best known example of the mass and the spring from physics books where the differential equation driving the process is the following

m*a(t) + c*v(t) + k*s(t) = u(t)

m = mass

a = acceleration

c = friction coeff.

v = speed

K = spring constant

s = position

u(t) is the input

Now let's suppose that any measure (s or v or a) is affected, after some time, by a drift or offset (I am not sure about my english). Then I need to remove the drift to get the proper measure. Looking in the internet it seemed to me that the most effective system is the Kalman algorithm in order to make proper estimation of this error affecting measure.

Is it so? And, even if I can transform the differential equation into the Laplace domain, and then in the discrete domain and so implement in the sw, I do not know how to integrate the "Kalman" within this implementation.

Best regards