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Structuring of Large-scale Complex Hybrid Systems: from Illustrative Analysis toward Modelization

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Abstract

System structuring is paramount to the development of large-scale complex hybrid systems (LCHS). However, there is no well-established and effective methodology for the structuring of LCHS. Using the approach of illustrating and abstracting, this paper investigates the structuring of LCHS based on a wide variety of applications. First, intrinsic attributes of LCHS are explored. Then, a unified framework-based analysis is made of six typical examples of LCHS, i.e. human brain-body systems, autonomous robot systems, autonomous fed-batch reactor systems, human-car driving systems, autonomous urban traffic systems, and autonomous production (manufacturing/industrial process) systems. In this way, common characteristics among typical examples, e.g., perception–decision link, distributing, nesting, hierarchy, multiple gradation and hybrid dynamics over a spectrum of time drivers, and, incidentally, wide application orientations of LCHS, are illustrated. Furthermore, after basic concepts for the modelization of LCHS are formulated, two novel general-purpose information-processing modules are proposed and constructed, called perception cube and decision spheroid. Based on them, a novel block diagram based model is originally proposed and established for LCHS.

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  1. School of Multimedia and Computing, Gloucestershire Business School, Cheltenham & Gloucester College of Higher Education, PO Box 220, The Park, Cheltenham, GL, 50 2QF, UK

    Huaglory Tianfield

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Tianfield, H. Structuring of Large-scale Complex Hybrid Systems: from Illustrative Analysis toward Modelization. Journal of Intelligent and Robotic Systems 30, 179–208 (2001). https://doi.org/10.1023/A:1008152518630

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