Nonlinear adaptive control method for treatment of uncertain hepatitis B virus infection

Adaptive Deformation Control for Elastic Linear Objects

This paper addresses the general problem of deformable linear object manipulation. The main application we consider is in the field of agriculture, for plant grasping, but may have interests in other tasks such as human daily activities and industrial production. We specifically consider an elastic linear object where one of its endpoints is fixed, and another point can be grasped by a robotic arm. To deal with the mentioned problem, we propose a model-free method to control the state of an arbitrary point that can be at any place along the object’s length. Our approach allows the robot to manipulate the object without knowing any model parameters or offline information of the object’s deformation. An adaptive control strategy is proposed for regulating the state of any point automatically deforming the object into the desired location. A control law is developed to regulate the object’s shape thanks to the adaptive estimation of the system parameters and its states. This method can track a desired manipulation trajectory to reach the target point, which leads to a smooth deformation without drastic changes. A Lyapunov-based argument is presented for the asymptotic convergence of the system that shows the process’s stability and convergence to desired state values. To validate the controller, numerical simulations involving two different deformation models are conducted, and performances of the proposed algorithm are investigated through full-scale experiments.

Fuzzy logic and Lyapunov-based non-linear controllers for HCV infection

Hepatitis C is the liver disease caused by the Hepatitis C virus (HCV) which can lead to serious health problems such as liver cancer. In this research work, the non‐linear model of HCV having three state variables (uninfected hepatocytes, infected hepatocytes and virions) and two control inputs has been taken into account, and four non‐linear controllers namely non‐linear PID controller, Lyapunov Redesign controller, Synergetic controller and Fuzzy Logic‐Based controller have been proposed to control HCV infection inside the human body. The controllers have been designed for the anti‐viral therapy in order to control the amount of uninfected hepatocytes to the desired safe limit and to track the amount of infected hepatocytes and virions to their reference value which is zero. One control input is the Pegylated interferon (peg‐IFN‐α) which acts in reducing the infected hepatocytes and the other input is ribavirin which blocks the production of virions. By doing so, the uninfected hepatocytes increase and achieve the required safe limit. Lyapunov stability analysis has been used to prove the stability of the whole system. The comparative analysis of the proposed nonlinear controllers using MATLAB/Simulink have been done with each other and with linear PID. These results depict that the infected hepatocytes and virions are reduced to the desired level, enhancing the rate of sustained virologic response (SVR) and reducing the treatment period as compared with previous strategies introduced in the literature.