This article presents optimal drug scheduling in chemotherapeutic treatment for eradication of cancerous cells while maintaining tolerable toxicity for the complete period of treatment. For this purpose a cascade control technique is designed wherein individual 2DOF FOPID controllers are employed to regulate drug concentration and toxicity. Conventional schemes fail to address the needs of divergent objectives of cancer chemotherapy which motivates the authors to employ a multi-objective optimization technique, NSGA-II to optimally tune the controller parameters. 2DOF FOPID, its integer order counterpart and PID control schemes are tested on cancer patient model for comparative analysis. The performance of proposed controller is evaluated on the basis of number of cancer cells and normal cells remaining at the end of treatment. Further robustness of the controller is analysed for parametric uncertainty in patient model and disturbance in infusion pump which affects the input drug dosages. The results reveal that proposed control scheme provides optimal drug scheduling and is significantly robust in the presence of uncertainty and disturbances.
|Number of pages||12|
|Journal||Journal of Intelligent and Fuzzy Systems|
|Publication status||Published - 2019|
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Artificial Intelligence