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Intelligent Robust Control of Autonomous Robot: Quantum Self-Organization of Imperfect Knowledge Bases—Experiment

  • ARTIFICIAL INTELLIGENCE
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Journal of Computer and Systems Sciences International Aims and scope

Abstract

The article discusses the information technology of a robust intelligent control system design based on quantum fuzzy inference. The application of the developed design methodology is based on the quantum self-organization of fuzzy controller’s imperfect knowledge bases and leads to an increase in the robustness of intelligent control systems in unpredicted situations. The results of mathematical modeling and physical experiment are compared using the example of an autonomous robot in the form of a “cart – pole” system. Experimental confirmation of the synergetic effect existence in the robust self-organized fuzzy controller formation from a finite number of non-robust fuzzy controllers in on-line has been demonstrated. The resulting effect is based on the existence of hidden quantum information extracted from the classical states of the controller’s time-varying gain coefficients processes schedule. The derived law of quantum information thermodynamics establishes the possibility to forming a thermodynamic control force due to the extracted amount of hidden quantum information and performing additional useful work, that guarantees the achievement of the control goal based on increasing the robustness of a self-organized quantum controller. 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-organized controller to extract the quantum information hidden in the responses of imperfect knowledge bases without violating the second thermodynamics information law for 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 quantum self-organization synergetic effect to imperfect knowledge bases.

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Authors and Affiliations

  1. Dubna State University, Institute of System Analysis and Management, 141980, Dubna, Russia

    A. G. Reshetnikov & S. V. Ulyanov

  2. Joint Institute for Nuclear Research, Meshcheryakov Laboratory of Information Technologies, 141980, Dubna, Russia

    A. G. Reshetnikov & S. V. Ulyanov

  3. Moscow State University of Geodesy and Cartography (MIIGAiK), 105064, Moscow, Russia

    V. S. Ulyanov

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  1. A. G. Reshetnikov
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Reshetnikov, A.G., Ulyanov, V.S. & Ulyanov, S.V. Intelligent Robust Control of Autonomous Robot: Quantum Self-Organization of Imperfect Knowledge Bases—Experiment. J. Comput. Syst. Sci. Int. 62, 884–902 (2023). https://doi.org/10.1134/S1064230723050131

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