Since the injection of the oncolytic viruses in the virotherapy process reduces the toxicity and drug resistance inherent in the chemotherapy; chemovirotherapy as a novel combination therapy has become an efficient cancer treatment. The primary purpose of this paper is to design a robust optimal control strategy for the chemovirotherapy through which the tumor density decreases to its stable condition with limited drug and virus delivery. This desired treatment should be responsive in the presence of input disturbances and parametric uncertainties. In this regard, an ODE (Ordinary Differential Equation) mathematical model of the chemovirotherapy process presenting the connection between the avascular tumor cells, immune cells, and treatment materials is utilized. H-infinity and DK iteration controllers are designed and implemented to the uncertain model, through the continuous and discrete procedures. By comparing the closed-loop simulations, discrete injection is found to be more effective (while is also more realistic in practice). The characteristics of an optimal treatment including the treatment frequency, drug and virus dosage, and suggested start time will be determined as the final results of this research.

由于在病毒治疗过程中注射溶瘤病毒会降低化学疗法固有的毒性和耐药性；化学治疗疗法作为一种新颖的联合疗法已成为一种有效的癌症治疗方法。本文的主要目的是设计一种化学疗法的鲁棒性最佳控制策略，通过该策略，肿瘤密度降低至稳定状态，同时限制药物和病毒的输送。在存在输入干扰和参数不确定性的情况下，这种期望的处理应具有响应性。在这方面，利用了化学疗法治疗过程的ODE（常微分方程）数学模型，该数学模型提出了无血管肿瘤细胞，免疫细胞和治疗材料之间的联系。H-infinity和DK迭代控制器是通过连续和离散过程设计并实现的，用于不确定模型。通过比较闭环模拟，发现离散注入更为有效（而在实践中也更为现实）。最佳治疗的特征，包括治疗频率，药物和病毒剂量以及建议的开始时间，将被确定为这项研究的最终结果。