Title :
Neural differential tracking control in cancer model
Author :
Aguilar, N. ; Cabrera, A. ; Chairez, I.
Abstract :
Immunotherapy refers to the use of natural and synthetic substances to stimulate the immune response. This document provides the description on the identification process for a particular cancer mathematical model under the immunotherapy treatment by differential neural networks (DNN) and sliding mode type observer techniques. The combination of these both techniques make available a close enough following between the estimate states given by the neural network and the cancer model dynamics: these are the interleukin-2, the tumor cells and the effector cells concentrations. Besides, a feedback control design is shown using the DNN´s estimated states and sliding mode control as a possible solution in the effective dose research for immunotherapy treatment. The numerical results derived by this method, implies the possibility to construct a real controller for cancer treatment using an IL-2 online sensor and an embedded system to implement the DNN scheme
Keywords :
cancer; control system synthesis; feedback; identification; neurocontrollers; observers; patient treatment; tracking; variable structure systems; IL-2 online sensor; cancer mathematical model; cancer model; differential neural network; effector cells; embedded system; feedback control design; identification; immune response; immunotherapy cancer treatment; interleukin-2; neural differential tracking control; sliding mode control; sliding mode type observer; state estimation; trajectory tracking; tumor cells; Cancer; Control systems; Feedback control; Mathematical model; Neural networks; Observers; Sensor systems; Sliding mode control; State estimation; Tumors;
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
DOI :
10.1109/ACC.2006.1656556