Solution to the problem of maintaining the efficiency and stability of the developing industry is subject to quick and sudden changes in the globalizing business environment has recently been of priority in the economic research. In the dynamic background of the institutional and innovative transformation in Russia activities of industrial enterprises are subject to risks of resource deterioration, competitive advantage loss and sliding towards bankruptcy. On this account it is an important challenge to develop and improve control technologies for stability of enterprises. For this purpose, we suggest theoretical, methodological and applied support of the design technology, including the involvement of both familiar tools of systems analysis, management, cybernetics, etc. and of innovative knowledge of nonlinear dynamics and self-organization theory which form the foundation for the interdisciplinary synergetic paradigm. Within the framework of its ideas, a logical explanation is given to the evolution of industrial enterprises from unstable equilibrium to stable non-equilibrium, as well as to qualitative modifications in their activities, in particular, those connected with the transition from a stable and less effective state to a more effective one. Along with this, from the perspective of the entropy approach and information theory, it becomes possible to give reasons for the nonlinear (exponential) dependence of the industrial enterprise performance on the amount of the accumulated information and to substantiate conditions for maintaining the stability of this effect, as well as the multi-factor analysis of dependence of financial and economic indicators of the enterprise performance on the knowledge achieved by the enterprise. In order to apply the concept and technology of managing the industrial enterprise stability, including the use of the heuristic algorithm (based on fuzzy sets), there has been developed and certified the software to monitor their stability which fulfills functions of the operational processing, visualization and understanding of change trends with regard to indicators observed.