Application of A Fuzzy Learning Intervention Approach to A Purine Metabolism Pathway Model Conference Paper

abstract

• Adaptive fuzzy control is used here to enforce a concentration level of some metabolite of a biological system representing a purine metabolism pathway model to track a reference trajectory in the presence of uncertainties. In contrast to the direct fuzzy controller, the adaptive fuzzy controller is able to reduce the variance of both the system's response and the controller's output. In this paper, we will apply the adaptive fuzzy intervention strategy to the purine metabolism pathway model in the presence of output noise, which is the source of the model's uncertainties, and carry out a sensitivity analysis of the controller's behavior. The simulation will also be carried out using the direct fuzzy controllers, as described in [1], and the results will be compared and analyzed. 2014 IEEE.

name of conference

• 2nd Middle East Conference on Biomedical Engineering

authors

• Nounou, Hazem
• Nounou, Mohamed

published proceedings

• 2014 Middle East Conference on Biomedical Engineering (MECBME)

author list (cited authors)

• Basha, N., Nounou, H. N., & Nounou, M. N.

citation count

• 0

complete list of authors

• Basha, Nour||Nounou, Hazem N||Nounou, Mohamed N

publication date

• February 2014

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Middle East Conference on Biomedical Engineering, MECBME  Journal

Digital Object Identifier (DOI)

• 10.1109/mecbme.2014.6783233

International Standard Book Number (ISBN) 13

• 9781479947997

start page

• 171

end page

• 174

URL

• http://dx.doi.org/10.1109/mecbme.2014.6783233