Constrained RMPC algorithms for time delay systems with parametric uncertainties: Application to the cancer combined therapy
| Autor: | Alireza Khayatian, Nasrin Goodarzi, Maryam Dehghani |
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| Rok vydání: | 2016 |
| Předmět: |
Mathematical optimization
Engineering Iterative method business.industry Quantitative Biology::Tissues and Organs 010102 general mathematics Process (computing) Combination chemotherapy 02 engineering and technology 01 natural sciences Quantitative Biology::Cell Behavior Cancer treatment Model predictive control Control theory 0202 electrical engineering electronic engineering information engineering Combined therapy Volume reduction 020201 artificial intelligence & image processing 0101 mathematics business Algorithm Parametric statistics |
| Zdroj: | 2016 24th Iranian Conference on Electrical Engineering (ICEE). |
| DOI: | 10.1109/iraniancee.2016.7585564 |
| Popis: | In this paper, a new MPC formulation for systems with known delayed states and a new iterative algorithm of robust model predictive control (RMPC) subject to polytopic-type parameter uncertainties and input constraints is presented. Control of delayed systems with parameter uncertainties is usually more complicated in presence of input constraints. MPC is an appropriate approach to handle this type of problems. Unlike existing MPC techniques, the main advantage of the proposed MPC algorithms is that they are simple to construct and therefore can be simply implemented in real applications. Combined chemotherapy and anti-angiogenic treatment is a novel medical approach used for cancer treatment in recent years. The paper shows the performance of proposed algorithms for tumor volume reduction in combined therapy subject to the necessary constraints on drugs dosage. In order to be more realistic, we consider model with delays in states that describe the process of angiogenesis-the growth of new blood vessels by budding from pre-existing vessels — and uncertainty in parameters. Finally, the simulation results illustrate the performance of the proposed algorithms. |
| Databáze: | OpenAIRE |
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