Intelligent distributed and supervised flow control methodology for production systems
Engineering Applications of Artificial Intelligence
International Journal of Applied Mathematics and Computer Science
A revisited approach to linear fuzzy regression using trapezoidal fuzzy intervals
Information Sciences: an International Journal
Information Sciences: an International Journal
Engineering Applications of Artificial Intelligence
A Midpoint--Radius approach to regression with interval data
International Journal of Approximate Reasoning
Robust PI controller design with respect to fuzzy sensitivity margins
Applied Soft Computing
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This paper aims at designing and analyzing an inverse controller for stable inversible (minimum phase) fuzzy interval linear and/or multilinear systems. The controller is designed from the fuzzy interval ranges of the system parameters using an α-cut methodology. Indeed, for a given α-cut of the fuzzy system parameters representing an uncertainty level, the control objective can be viewed as maintaining the system output within a tolerance envelope, around the exact trajectory, specified by the degree of preference α on the fuzzy trajectory. The stability is ensured in the way that the controller restricts the system output divergence within the tolerance envelope. The validity of the proposed method is illustrated by simulation examples.