Authors: N. Sozhamadevi; S. Sathiyamoorthy
Addresses: Department of Electronics and Communication Engineering, BIT Campus, Anna University, Tiruchirappalli – 620024, Tamil Nadu, India ' Department of Electronics and Instrumentation Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India
Abstract: In this paper, we discuss the theory and design of the probabilistic fuzzy inference system, one that model and minimise the effects of rule uncertainties, i.e., existing randomness in many real world systems. This approach ascends from the combination of the concepts of degree of truth and probability of truth in a unique framework. This combination is carried out both in fuzzy sets and fuzzy rules, which leads to probabilistic fuzzy sets and probabilistic fuzzy rules. Using these probabilistic elements, an innovative probabilistic fuzzy logic system is obtained as a fuzzy probabilistic model of a complex non-deterministic system. We designed probabilistic fuzzy inference system for modelling the CSTR process, which shows dynamic nonlinearity and demonstrated its upgraded performance over the conventional fuzzy inference system.
Keywords: continuous stirred tank reactors; CSTR; probabilistic fuzzy sets; PFS; probabilistic fuzzy inference system; PFIS; probabilistic fuzzy relations; PFR; probabilistic modelling; fuzzy logic; intelligent modelling; process modelling; rule uncertainties.
International Journal of Automation and Control, 2015 Vol.9 No.2, pp.143 - 157
Available online: 22 Jun 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article