Direct adaptive interval type-2 fuzzy logic controller for the multivariable anaesthesia system

Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia

“…Therefore we can use the two errors to roughly compare the performance of the two controllers. By comparison we can M a n u s c r i p t 50 find that even the worst case of the 42-IT2-SOFLC and 42-GT2-SOFLC can still produce a lower error than the best case of the direct adaptive IT2-FLC in [16]. Nevertheless, it should be noted that the RMSE measured for direct adaptive IT2-FLC also counted the settling stage, which leads to a larger overall error.…”

“…El-Bardini et al proposed a direct adaptive IT2-FLC in [16] applied to the same scenario as our study. The direct adaptive IT2-FLC uses a predefined rule-base and tunes the centers of the output MFs of fired rules in response to deviations from the desired control behaviour.…”

“…Pharmacological modeling is commonly used to describe the metabolism of such drugs [16] which can be used as a basis to create a mathematical model. Pharmacological modeling comprises of two main categories which are: Pharmacokinetics (PK), the concentration of drugs in the blood as a function of time and dose schedule interpreted mathematically via compartmental models representing the metabolism of the drug in different parts of the body;…”

“…This is due to the fact that type-2 fuzzy sets have more design degrees of freedoms, which are able to handle higher orders of possible real world uncertainties and hence potentially contribute to producing more accurate and stable control performances. Previous work by El-Bardini and El-Nagar [16] has developed a direct adaptive interval type-2 FLC for controlling the multivariable anesthesia system to overcome the uncertainty problem introduced by large inter and intra-individual variability of the patient's parameters. This adaptive controller uses predefined rule-bases for each control signal and expert initialized interval type-2 fuzzy sets.…”

Derivation and stability analysis of the analytical structures of the interval type-2 fuzzy PID controller

“…Therefore, Mendel [7] has been proposed a special type of T2-FS called interval T2-FSs (IT2-FSs) in which the output of interval type-2 fuzzy is uncertain with an interval. The interval T2-FLSs (IT2-FLSs) has been successfully implemented in controller design [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. These efforts focus on the controllers that have been used as black box controllers in that their input-output mathematical relations are unknown.…”