Nonlinear optimization with a matrix form of constraints

I'm trying to solve a nonlinear optimization problem with a matrix for linear constratins using MKL (Intel C++ 16.0).

Although aware that some bounds can be set for each variable x_i, e.g., LB_i <= x_i <= UB_i (like the usage example),

not quite sure how to impose additional constratins in matrix forms such that: Ax = b where A is m-by-n matrix; i.e. there are m constraints for variables x.

I'm actually trying to make a transition from using 'fminon' (http://kr.mathworks.com/help/optim/ug/fmincon.html) function of MATLAB to using MKL.

Is there any way? Thanks.