Premium
PID, Predictive and fuzzy temperature control for nuclear magnetic resonance spectroscopy experiments
Author(s) -
Grossi P.,
Scattolini R.
Publication year - 1991
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.4480050604
Subject(s) - pid controller , model predictive control , control theory (sociology) , temperature control , controller (irrigation) , control engineering , fuzzy logic , fuzzy control system , regulator , computer science , engineering , control (management) , chemistry , artificial intelligence , agronomy , biology , biochemistry , gene
Temperature control inside the probe of an NMR spectrometer is dealt with. First a simple model of the system is derived by means of step response experiments. Then four control algorithms are implemented and compared. Specifically, a PID regulator is first synthesized and applied to the real plant. Then, in order to cope with the non‐linearity of the plant, two adaptive predictive control algorithms are implemented, namely the generalized predictive control and the constrained receding horizon predictive control algorithms. They both show superior performance with respect to PID for control of a simulated plant model and of the real plant. Finally a feasibility study is carried out for a fuzzy controller; its unsatisfactory behaviour in simulation prevents one from applying it to the plant.