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Alamir M.,Martin Control Systems
Journal of Theoretical Biology | Year: 2015

This paper proposes a general framework for probabilistic certification of cancer therapies. The certification is defined in terms of two key issues which are the tumor contraction and the lower admissible bound on the circulating lymphocytes which is viewed as indicator of the patient health. The certification is viewed as the ability to guarantee with a predefined high probability the success of the therapy over a finite horizon despite of the unavoidable high uncertainties affecting the dynamic model that is used to compute the optimal scheduling of drugs injection. The certification paradigm can be viewed as a tool for tuning the treatment parameters and protocols as well as for getting a rational use of limited or expensive drugs. The proposed framework is illustrated using the specific problem of combined immunotherapy/chemotherapy of cancer. © 2015 Elsevier Ltd. Source


Alamir M.,Martin Control Systems
2013 European Control Conference, ECC 2013 | Year: 2013

In this paper, a method is proposed for on-line monitoring of the control updating period in fast-gradient-based Model Predictive Control (MPC) schemes. Such schemes are currently under intense investigation as a way to accommodate for real-time requirements when dealing with systems showing fast dynamics. The method needs cheap computations that use the algorithm on-line behavior in order to recover the optimal updating period in terms of cost function decrease. A simple example of constrained triple integrator is used to illustrate the proposed method and to assess its efficiency. © 2013 EUCA. Source


Alamir M.,Martin Control Systems | Welsh J.S.,University of Newcastle | Goodwin G.C.,University of Newcastle
Automatica | Year: 2011

In this paper, a new dynamic model describing the epileptic seizure initiation through transition from interictal to ictal state in a brain predisposed to epilepsy is suggested. The model follows Freeman's approach where the brain is viewed as a network of interconnected oscillators. The proposed nonlinear model is experimentally motivated and relies on changes in synaptic strength in response to excitatory spikes. This model exhibits a threshold beyond which a bifurcation toward a short-term plasticity state occurs leading to seizure onset. A resulting explanatory assumption is that when considering epilepsy, brain regions are characterized by abnormally low thresholds toward short-term synaptic plasticity. It is shown by simulation that the proposed model enables some experimentally observed qualitative features to be reproduced. Moreover, a preliminary discussion on the impact of the underlying assumptions on the fundamental issue of seizure control is proposed through an EEG based feedback control scheme. © 2011 Elsevier Ltd. All rights reserved. Source


Alamir M.,Martin Control Systems | Rahmani M.A.,Schneider Electric | Gualino D.,Schneider Electric
Journal of Process Control | Year: 2014

Thermodynamic engines are focusing increasing attention in the context of solar-based electric power generation. Knowledge-based models of such engines are sometimes difficult to derive and when they are available, their simulation may be numerically a rather heavy task given the control updating period that may be needed. In the present work a generic nonlinear identification framework that enables the dynamics of the key quantities of a thermodynamic engine to be captured is proposed. Such a fast model can then be used in the simulation and the control design stage of the whole electric power generation station. The proposed identification framework is validated on a recently developed knowledge-based model of a beta-type Stirling engine with rhomic-drive mechanism. © 2014 Elsevier Ltd. All rights reserved. Source


Seuret A.,Martin Control Systems | Peet M.M.,Arizona State University
IEEE Transactions on Automatic Control | Year: 2013

This technical brief proposes a new approach to stability analysis of linear systems with sampled-data inputs or channels. The method, based on a variation of the discrete-time Lyapunov approach, provides stability conditions using functional variables subject to convex constraints. These stability conditions can be solved using the sum of squares methodology with little or no conservatism in both the case of synchronous and asynchronous sampling. Numerical examples are included to show convergence. © 1963-2012 IEEE. Source

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