Robust Evolving Cloud-based Controller (ReCCo)

Andonovski, Goran and Angelov, Plamen Parvanov and Blazic, Saso and Skrjanc, Igor (2017) Robust Evolving Cloud-based Controller (ReCCo). In: 2017 Evolving and Adaptive Intelligent Systems (EAIS). IEEE, pp. 1-6. ISBN 9781509064458

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Abstract

This paper presents an autonomous Robust Evolving Cloud-based Controller (RECCo). The control algorithm is a fuzzy type with non-parametric (cloud-based) antecedent part and adaptive PID-R consequent part. The procedure starts with zero clouds (fuzzy rules) and the structure evolves during performing the process control. The PID-R parameters of the first cloud are initialized with zeros and furthermore, they are adapted on-line with a stable adaptation mechanism based on Lyapunov approach. The RECCo controller does not require any mathematical model of the controlled process but just basic information such as input and output range and the estimated value of the dominant time constant. Due to the problem space normalization the design parameters are fixed. The proposed controller with the same initial design parameters was tested on two different simulation examples. The experimental results show the convergence of the adaptive parameters and the effectiveness of the proposed algorithm.

Item Type:
Contribution in Book/Report/Proceedings
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ID Code:
131901
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Deposited On:
20 Mar 2019 12:45
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 07:04