DocumentCode :
900723
Title :
Development and analysis of a feedback treatment strategy for parturient paresis of cows
Author :
Padhi, Radhakant ; Balakrishnan, Sivasubramanya N.
Author_Institution :
Dept. of Mech. & Aerosp. Eng. & Eng. Mech., Univ. of Missouri Rolla, MO, USA
Volume :
12
Issue :
1
fYear :
2004
Firstpage :
52
Lastpage :
64
Abstract :
An intelligent on-line feedback treatment strategy based on nonlinear optimal control theory is presented for the parturient paresis of cows. A limitation in the development of an existing nonlinear mathematical model for the homogeneous system is addressed and further modified to incorporate a control input. A neural network based optimal feedback controller is synthesized for the treatment of the disease. Detailed studies are used to analyze the effectiveness of a feedback medication strategy and it is compared with the current ´impulse´ strategy. The results show that while the current practice may fail in some cases, especially if it is carried out before the condition of a patient deteriorates, the proposed continuous medication process may be initiated at any time. Moreover the proposed on-line continuous infusion strategy never leads to severe hypercalcemic problems, thereby avoiding an associated disastrous consequence of cardiac arrest. A comparison study with linear quadratic regulator theory brings out the advantages of the nonlinear control synthesis approach.
Keywords :
control system synthesis; diseases; intelligent control; mathematical analysis; medical control systems; neural nets; nonlinear control systems; optimal control; veterinary medicine; animal disease; dairy cows; disease treatment; feedback treatment strategy; linear quadratic regulator theory; neural network; nonlinear control synthesis approach; nonlinear mathematical model; nonlinear optimal control theory; on-line continuous infusion strategy; optimal feedback controller; parturient paresis; Adaptive control; Control system synthesis; Cows; Feedback; Mathematical model; Medical control systems; Neural networks; Neurofeedback; Nonlinear control systems; Optimal control;
fLanguage :
English
Journal_Title :
Control Systems Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-6536
Type :
jour
DOI :
10.1109/TCST.2003.821962
Filename :
1268051
Link To Document :
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