Paper Info
Title
Analysis of adaptation law of the robust evolving cloud-based controller
Abstract
In this paper we propose a performance analysis of the robust evolving cloud-based controller (RECCo) according to the different initial scenarios. RECCo is a controller based on fuzzy rule-based (FRB) systems with non-parametric antecedent part and PID type consequent part. Moreover, the controller structure (the fuzzy rules and the membership function) is created in online manner from the data stream. The advantage of the RECCo controller is that do not require any a priory knowledge of the controlled system. The algorithm starts with zero fuzzy rules (zero data clouds) and evolves/learns during the process control. Also the PID parameters of the controller are initialed with zeros and are adapted in online manner. According to the zero initialization of the parameters the new adaptation law is proposed in this article to solve the problems in the starting phase of the process control. Several initial scenarios were theoretically propagated and experimentally tested on the model of a heat-exchanger plant. These experiments prove that the proposed adaptation law improve the performance of the RECCo control algorithm in the starting phase.
Year
DOI
Venue
2015
10.1109/EAIS.2015.7368793
2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)
Keywords
DocType
ISSN
adaptation law,robust evolving cloud-based controller,fuzzy rule-based systems,FRB systems,PID type consequent part,controller structure,RECCo controller,controlled system,zero fuzzy rules,zero data clouds,process control,PID parameters,zero initialization,heat exchanger plant,RECCo control algorithm
Conference
2330-4863
Citations 
PageRank 
References 
3
0.43
26
Authors
4
Name
Order
Citations
PageRank
Goran Andonovski1283.97
Saso Blazic215129.21
Plamen Angelov395467.44
Igor Skrjanc435452.47