Abstarct: Due to the increasing prevalence of cancer and failure in its treatment, it has led to different approaches to investigate the failure causes and the way to remedy it. It is important to choose an appropriate treatment protocol and the way to apply it. In this study, by studying the models of cancer treatment and considering their accuracy and model flexibility in their application, two models of chemotherapy and immunotherapy have been used to considered and simulated. Firstly, to consider the effects of each treatment, we simulated them separately and then analyzed the results. Finally, to improve the quality of treatment by combining chemotherapy and immunotherapy, we compared the new results with previous treatment protocols which were independently administered. On the other hand, to reduce the treatment duration, side effects, medical costs and maintaining the health of the patients, a method baxsed on optimal control was presented, that while reducing the number of cancer cells and maintaining stability of patient’s health equilibrium point, has also considered the above cases. This method, which is baxsed on Lyapunov stability, linearizes the nonlinear dynamics of cancer, and is obtained by solving the state-dependent riccati equations, is called SDRE. In this method, by considering biological constraints, a control system was designed so as to determine the optimal time and volume of injection, and optimal treatment regimen. Simulations were done for three different scenarios: without treatment, with treatment and treatment with control input; finally, the importance of using this method in reducing system errors besides its flexibility compared to the other methods was discussed. Moreover, the robustness of this method against parametric variations, was investigated.