New class of matrix gradient techniques is described on the basis of relaxation function apparatus. This class generalises classical gradien methods, Newtonian methods and Levenberg–Markguardt methods. Distinctive from classical, methods developed keep convergence for nonconvex problems of nonlinear programming in high stiffness of criterion functional conditions.