Toward a model-free feedback control synthesis for treating acute inflammation

Ouassim Bara (1) , Michel Fliess (2, 3) , Cédric Join (4, 3, 5) , Judy Day (6) , Seddik M Djouadi (1)

1 Department of Electrical Engineering and Computer Science [Knoxville]
2 LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
3 AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques
4 CRAN - Centre de Recherche en Automatique de Nancy
5 NON-A-POST - Non-Asymptotic estimation for online systems
6 Department of Mathematics University of Tennessee Knoxville

An effective and patient-specific feedback control synthesis for inflammation resolution is still an ongoing research area. A strategy consisting of manipulating a pro and anti-inflammatory mediator is considered here as used in some promising model-based control studies. These earlier studies, unfortunately, suffer from the difficultly of calibration due to the heterogeneity of individual patient responses even under similar initial conditions. We exploit a new model-free control approach and its corresponding "intelligent" controllers for this biomedical problem. A crucial feature of the proposed control problem is as follows: the two most important outputs which must be driven to their respective desired states are sensorless. This difficulty is overcome by assigning suitable reference trajectories to the other two outputs that do have sensors. A mathematical model, via a system of ordinary differential equations, is nevertheless employed as a "virtual" patient for in silico testing. We display several simulation results with respect to the most varied situations, which highlight the effectiveness of our viewpoint.

Keywords: Immune systems; Intelligent controllers; Inflammatory response; Model-free control

Domains: Life Sciences [q-bio]; Quantitative Methods [q-bio.QM]; Life Sciences [q-bio]; Immunology; Computer Science [cs]; Bioinformatics [q-bio.QM]; Computer Science [cs]; Biotechnology; Computer Science [cs]; Automatic Control Engineering; Engineering Sciences [physics]; Automatic; Computer Science [cs]; Systems and Control [cs.SY]; Mathematics [math]; Optimization and Control [math.OC]; Computer Science [cs]; Artificial Intelligence [cs.AI]; Statistics [stat]; Machine Learning [stat.ML]

Ouassim Bara, Michel Fliess, Cédric Join, Judy Day, Seddik M Djouadi. Toward a model-free feedback control synthesis for treating acute inflammation. Journal of Theoretical Biology, 2018, 448, pp.26-37. ⟨10.1016/j.jtbi.2018.04.003⟩. ⟨hal-01756743⟩