Abstract
In this research work, a Three-Dimensional Cancer model (TDCM) has been used and nonlinear controllers; Lyapunov Redesign, Synergetic and Sliding Mode based controllers have been designed in order to reduce the growth of tumor cells to a level where they become harmless, to maintain the hunting predator cells to their maximum possible value and to retain resting predator cells to 40% of the hunting predator cells. The proposed controllers have been developed for chemotherapy and their effect on different cells has been studied. Asymptotic stability of the proposed controllers has been studied using Lyapunov stability theory. Theoretical analysis has been supported by simulation results using MATLAB/Simulink. Under the proposed controllers, the system behaves very nicely even in the presence of un-modeled disturbances and noise.
Highlights
Infectious diseases portrayed by uncontrolled cell development are called cancer
In this paper we have proposed three nonlinear controllers namely; Lyapunov Redesign, Synergetic and Sliding Mode based controllers using Three-Dimensional Cancer model (TDCM) for reducing the growth of tumor cells to a level where they become harmless, maintaining the hunting predator cells to their maximum possible value and retaining resting predator cells to 40% of the hunting predator cells
The tumor cells develop at the rate r1 without any effect of hunting and resting predator cells with maximum carrying capacity of k1. a12 and a13 are the rate at which tumor cells are being killed by the hunting and resting predator cells respectively
Summary
Infectious diseases portrayed by uncontrolled cell development are called cancer. Unsatisfactory performance of immune system against chaotic tumor cells and their disordered development prompts harm and even death to patients. In one of the recent works, cell population exhibited a chaotic property which is highlighted by state-space linearization based on lie algebra using a TDCM by [1] It included a typical population of tissue cells to perform a phase space analysis and used optimal control theory to study. I. Lodhi et al.: Nonlinear Control for Growth of Cancerous Tumor Cells the impact of chemotherapeutic treatment [13]. Lodhi et al.: Nonlinear Control for Growth of Cancerous Tumor Cells the impact of chemotherapeutic treatment [13] It analyzed the development of tumor cell in the presence of the cytokine IL-2 and the resting predator cells. One can discover different cancer-immune interaction models along with their dynamical analysis These models incorporate distinctive cell growth and share fundamental qualities. Simulation results using MATLAB/Simulink have been shown in section IV and section V presents the conclusion
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
