A unified real-time approximate reasoning approach for use in intelligent control Part 1. Theoretical development

Abstract

Taking account of the fuzzy nature of human decision making processes and real-time properties, this paper establishes a unified approximate reasoning model based on possibility theory rather than on relational matrix computation. Both fuzzy and random uncertainties can be coped with in the model. In the case of sensor-based situations, a simpler reasoning scheme is derived by introducing the concepts of matching measures. The proposed models may provide another possibility for on-line reasoning in real-time expert system applications. In Part 1, the theoretical foundations are provided, while in Part 2 their application to multivariate blood pressure control is described.