Applied Quantum Soft Computing IT
SW & HW Sustainable Platform of Robust Intelligent Robotic Controllers
Abstract
The information technology of a robust intelligent control system design based on quantum fuzzy inference is considered. The application of the developed design methodology is based on the quantum self-organization of imperfect knowledge bases of fuzzy controllers and leads to an increase in the robustness of intelligent control systems in unforeseen situations. The results of mathematical modeling and physical experiment are compared using the example of an autonomous robot in the form of an “cart - pole” system. Experimental confirmation of the existence of a synergetic effect of the formation of a robust self-organizing fuzzy controller from a finite number of non-robust fuzzy controllers in on line has been obtained. The resulting effect is based on the existence of hidden quantum information extracted from the classical states of the processes of time-varying gain coefficients schedule of regulators. At the same time, the amount of useful work performed by the control object (at the macro level) exceeds the amount of work spent (at the micro level) by a quantum self-organizing regulator to extract quantum information hidden in the reactions of imperfect knowledge bases without violating the second information law of thermodynamics of open quantum systems with information exchange of entangled (super-correlated) states. A concrete example of an autonomous robot is given, demonstrating the existence of a synergetic effect of quantum self-organization of imperfect knowledge bases.
A generalized strategy for designing intelligent robust control systems based on quantum / soft computing technologies is described, which increase the reliability of hybrid intelligent controllers by providing the ability to self-organize. The main attention is paid to increasing the level of robustness of intelligent control systems in unpredictable control situations with demonstration by illustrative examples. A SW & HW platform and support tools for a supercomputer accelerator for modeling quantum algorithms on a classical computer are described.
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