How to minimize a vectorized function in 1 variable?

This problem is originally a multi objective problem but using scalarization it can be transformed to the following:

Min: -p'*x + u*x'*V*x       
subject to 1*x=1            

u is the risk aversion index that I wish to vary from .1 to 100
V is a (4x4) variance covariance matrix 
p is the (4x1) expected return vector, p' is (1x4)
x is the (4x1) asset weight vector I wish to solve for
** the sum of x is 1 (the only constraint)

I've tried the fmincon function but don't know how to set it up.

[Walter Roberson]

Did you say "subject to 1*x=1" ? That would require x to be 1.