Noise parameter estimation for non-singleton fuzzy logic systems

Pekaslan, Direnc; Garibaldi, Jonathan M.; Wagner, Christian

Abstract

Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced variants such as centroid-based NSFLSs have the capacity to handle known quantities of uncertainty, thus far, the actual level of uncertainty has had to be defined a priori - i.e. prior to run time of a system or controller. This paper does not focus on such advances within the architecture of NSFLSs, but focuses on a novel two-stage approach for uncertainty handling in fuzzy logic systems which integrates: (i) estimation of noise levels and (ii) the appropriate handling of the noise based on this estimate, by means of a dynamically configured NSFLS. As initial evaluation of the approach, two chaotic nonlinear time series (Mackey-Glass and Lorenz), as well as a real-world Darwin sea level pressure series prediction fuzzy logic systems are implemented and compared to commonly used procedures. The results indicate that the proposed strategy of integrating uncertainty/noise estimation with the capacity of non-singleton fuzzy logic systems has the potential to deliver performance benefits in real-world applications without requiring a priori information on noise levels and thus delivers a first step towards smart, noise-adaptive non-singleton fuzzy logic systems and controllers.

Citation

Pekaslan, D., Garibaldi, J. M., & Wagner, C. (in press). Noise parameter estimation for non-singleton fuzzy logic systems

• Conference Name: IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2018)
• End Date: Oct 10, 2018
• Acceptance Date: Jun 17, 2018
• Deposit Date: Jul 27, 2018
• Peer Reviewed: Peer Reviewed
• Public URL: http://eprints.nottingham.ac.uk/id/eprint/53167
• Related Public URLs: http://www.smc2018.org/; https://ieeexplore.ieee.org/
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