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

• Published in: Journal of theoretical biology 2018-07, Vol.448, p.26-37
• Main Authors: Bara, Ouassim, Fliess, Michel, Join, Cédric, Day, Judy, Djouadi, Seddik M.
• Format: Article
• Language: English
• Subjects: Acute Disease; Artificial Intelligence; Automatic; Automatic Control Engineering; Bioinformatics; Biotechnology; Computer Science; Computer Simulation; Engineering Sciences; Feedback; Humans; Immune systems; Immunology; Inflammation - therapy; Inflammatory response; Intelligent controllers; Life Sciences; Machine Learning; Mathematics; Model-free control; Models, Theoretical; Optimization and Control; Quantitative Methods; Statistics; Systems and Control
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2018.04.003

•A new data driven control approach is used to control an inflammatory immune response.•The performance of the approach with respect to parameter variability and different initial conditions of a large set of virtual patients is evaluated with simulation.•The results in the presence of measurements noise are also depicted. The robustness of the control through the use of a single reference trajectory is observed. 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.