Industrial robots often operate in conditions of their parameters substantial variation that causes variation of their control systems characteristic equations coefficients values, thus generating the equations families. Analysis of the dynamic systems characteristic polynomial families stability, the stable polynomials and polynomial families synthesis represent complicated and important task (Polyak, 2002, a). Within the parametric approach to the problem the series of the effective methods for analysis have been developed (Bhattaharyya et al., 1995; Polyak, 2002, a). In this way, V. L. Kharitonov (Kharitonov, 1978) proved that for the interval uncertain polynomials family asymptotic stability verification it is necessary and enough to verify only four polynomials of the family with the definite constant coefficients. In the works of Y. Z. Tsypkin and B. T. Polyak the frequency approach to the polynomially described systems robustness was offered (Polyak & Tsypkin, 1990; Polyak & Scherbakov, 2002; Tsypkin & Polyak, 1990; Tsypkin, 1995). This approach comprises the robust stability criteria for linear continuous systems, the methods for calculating the maximal disturbance swing for the nominal stable system on the base of the Tsypkin – Polyak hodograph. These results were generalized to the linear discrete systems (Tsypkin & Polyak, 1990). The robust stability criterion for the relay control systems with the interval linear part was obtained (Tsypkin, 1995). The super-stable linear systems were considered (Polyak & Scherbakov, 2002). The problem for calculating the polynomial instability radius on the base of the frequency approach is investigated (Kraev & Fursov, 2004). The technique for composing the stability domain in the space of a single parameter or two parameters of the system with the D-decomposition approach application is developed (Gryazina & Polyak. 2006). The method for definition of the nominal polynomial coefficients deviations limit values, ensuring the hurwitz stability, has been offered (Barmish, 1984). The task here is reduced to the single-parameter optimization problem. The similar tasks are solved by A. Bartlett (Bartlett et al., 1987) and C. Soh (Soh et