Tumor Treatment Protocol by Using Genetic Algorithm Based Bernstein Polynomials and Sliding Mode Controller

Abstract

Life threatening nature of cancer and toxic effects of chemotherapy demand for an optimal design of treatment protocol. The main objective of treatment design is to maintain adequate health of patient while administering a continuous chemo dose for effective decimation of cancer. Mathematical model adopted in this paper is first order nonlinear coupled ordinary differential equation (NCODE) relating tumor, effector immune and normal cells under effect of chemotherapy. This paper primarily utilizes the Bernstein polynomial with genetic algorithm based coefficient tuning for solution of the tumor model. Secondarily sliding mode controller (SMC) is used as optimal control for normal and immune cells boosting in addition to escalated tumor minimization. The hybrid approach used in this research produces a potent minimization of cancer. Application of SMC ensures normal cells concentration well above the critical threshold; hence a continuous treatment dose is viable. Proposed methodology enhances the effect of chemotherapy over cancer while maintaining healthy state of patient.

Keywords

• Bernstein polynomial (BSP)
• nonlinear coupled ordinary differential equation (NCODE)
• genetic algorithm (GA)
• optimization
• sliding mode controller (SMC)