Iterative method for estimating the robust domains of attraction of non-linear systems: Application to cancer chemotherapy model with parametric uncertainties

Abstract In this paper, we present an iterative procedure method for estimating the robust domains of attraction of non-linear systems. This method is based on the approximation of the uncertain non-linear system with a parameters-dependent Convex Difference Inclusions (CDI) system and the classical iterative methods for linear systems, which are introduced in this paper. A robust one-step operator computing a sequence of convex sets is derived, and the polyhedral case is discussed. An algorithm summarizing the iterative procedure based on the robust one-step operator is given, which is the theoretical contribution of this paper. This method is applied to cancer chemotherapy model considering parametric uncertainties and it is shown that drastic reduction of the robust domain of attraction of the cancer chemotherapy model has happened and this is caused by the presence of parametric uncertainties. It is also proved that the aggressive chemotherapy is not the effective treatment for all the patients.

[1]  Andrey V. Savkin,et al.  Application of optimal control theory to analysis of cancer chemotherapy regimens , 2002, Syst. Control. Lett..

[2]  Mazen Alamir,et al.  On Probabilistic Certification of Combined Cancer Therapies Using Strongly Uncertain Models , 2015, Journal of theoretical biology.

[3]  Riccardo Scattolini,et al.  A stabilizing model-based predictive control algorithm for nonlinear systems , 2001, Autom..

[4]  Mazen Alamir,et al.  Domain of attraction estimation of cancer chemotherapy model affected by state proportional uncertainty , 2016, 2016 European Control Conference (ECC).

[5]  A. Radunskaya,et al.  Mixed Immunotherapy and Chemotherapy of Tumors: Modeling, Applications and Biological Interpretations , 2022 .

[6]  E. Gilbert,et al.  Theory and computation of disturbance invariant sets for discrete-time linear systems , 1998 .

[7]  Mirko Fiacchini Convex Difference Inclusions for Systems Analysis and Design. Inclusiones Convexas para el Análisis y el Diseño. , 2013 .

[8]  P. Hahnfeldt,et al.  Tumor development under angiogenic signaling: a dynamical theory of tumor growth, treatment response, and postvascular dormancy. , 1999, Cancer research.

[9]  E K Afenya,et al.  Some perspectives on modeling leukemia. , 1998, Mathematical biosciences.

[10]  R. B. Martin,et al.  Optimal control drug scheduling of cancer chemotherapy , 1992, Autom..

[11]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[12]  G. Chesi Domain of Attraction: Analysis and Control via SOS Programming , 2011 .

[13]  A. Murugan,et al.  Chemotherapy for tumors: an analysis of the dynamics and a study of quadratic and linear optimal controls. , 2007, Mathematical biosciences.

[14]  J. Aubin,et al.  Differential inclusions set-valued maps and viability theory , 1984 .

[15]  E. F. Camacho,et al.  On the computation of convex robust control invariant sets for nonlinear systems , 2010, Autom..

[16]  Ami Radunskaya,et al.  A mathematical tumor model with immune resistance and drug therapy: an optimal control approach , 2001 .

[17]  David Q. Mayne,et al.  Invariant approximations of the minimal robust positively Invariant set , 2005, IEEE Transactions on Automatic Control.

[18]  Franco Blanchini,et al.  Set-theoretic methods in control , 2007 .

[19]  T. Alamo,et al.  Convex invariant sets for discrete-time Lur'e systems , 2009, Autom..

[20]  丸山 徹 Convex Analysisの二,三の進展について , 1977 .

[21]  J. M. Murray,et al.  Optimal drug regimens in cancer chemotherapy for single drugs that block progression through the cell cycle. , 1994, Mathematical biosciences.

[22]  Mazen Alamir,et al.  Robust feedback design for combined therapy of cancer , 2014 .

[23]  E. Afenya,et al.  Acute leukemia and chemotherapy: a modeling viewpoint. , 1996, Mathematical biosciences.

[24]  Jean-Pierre Aubin,et al.  Viability theory , 1991 .

[25]  D. Bertsekas Infinite time reachability of state-space regions by using feedback control , 1972 .

[26]  Panos M. Pardalos,et al.  Convex optimization theory , 2010, Optim. Methods Softw..

[27]  K. T. Tan,et al.  Linear systems with state and control constraints: the theory and application of maximal output admissible sets , 1991 .

[28]  Mazen Alamir,et al.  Invariance-based analysis of cancer chemotherapy , 2015, 2015 IEEE Conference on Control Applications (CCA).

[29]  Eduardo F. Camacho,et al.  Invariant sets computation for convex difference inclusions systems , 2012, Syst. Control. Lett..

[30]  G. W. Swan Role of optimal control theory in cancer chemotherapy. , 1990, Mathematical biosciences.

[31]  S Chareyron,et al.  Mixed immunotherapy and chemotherapy of tumors: feedback design and model updating schemes. , 2009, Journal of theoretical biology.

[32]  Urszula Ledzewicz,et al.  Optimal control for combination therapy in cancer , 2008, 2008 47th IEEE Conference on Decision and Control.