Questions on Kalman filter...

I have the following problem to which I am thinking of applying Kalman
filter:

x1(k+1) = x1(k) + u1(k)-u2(k)+w1(k)
x2(k+1) = x2(k) + u2(k)-u3(k)+w2(k)
y(k) = x1(k) + x2(k) + v(k)

w1,w2,v are noises. u1, u2 are control actions. u3 is a disturbance.
u1, u2 and u3 are known to only upto a certain level and they are
corrupted by noises which I am thinking of modeling as being included
in w1 and w2. y is the observation and I need to estimate the two
states x1 and x2.

I have read thro' some introductory material on Kalman filters but have
the following unanswered questions:

1. Is the above formulation such that Kalman filter can be applied?
Specifically, something bothers me about estimating two variables (x1,
x2) from one measurement y which is the sum of the two variables.

2. If I can apply KF, then what is the structure of the covariance
matrix Q of the state noises w1, w2? Note that the presence of u2 in
both x1 and x2 equations will correlate w1 and w2 and hence I expect Q
to have nonzero off-diagonal elements? Any suggesstions on how to
estimate this matrix from the noise characterizations of u1,u2 and u3?

3. If I can apply KF, an additional requirement I have is that state
estimates should be >= 0 at all times. Any idea on how to satisfy this
constraint?

TIA