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In this paper, we consider a class of affine control systems and propose a new structural feedback linearization technique. This relatively simple approach involves a generic linear-type control scheme and follows the classic failure detection methodology. The robust linearization idea proposed in this contribution makes it possible an effective rejection of nonlinearities that belong to a specific class of functions. The nonlinearities under consideration are interpreted here as specific signals that affect the initially given systems dynamics. The implementability and efficiency of the proposed robust control methodology is illustrated via the attitude control of a PVTOL. AbstractIn this paper, we consider a class of affine control systems and propose a new structural feedback linearization technique. This relatively simple approach involves a generic linear-type control scheme and follows the classic failure detection methodology. The robust linearization idea proposed in this contribution makes it possible an effective rejection of nonlinearities that belong to a specific class of functions. The nonlinearities under consideration are interpreted here as specific signals that affect the initially given systems dynamics. The implementability and efficiency of the proposed robust control methodology is illustrated via the attitude control of a Planar Vertical Take Off Landing (PV-TOL) system. Notation. The following notation is used through this paper.• Script capitals V , W , . . . denote finite dimensional linear spaces with elements v, w, . . .. The expression V ≈ W stands for dim (V ) = dim (W ). Moreover, when V ⊂ W , W V or W /V stands for the quotient space W modulo V . Next, V κ denotes the Cartesian product V × · · · × V (κ times). By X : V → W , we denote a linear transformation operating from V to W . As usually, Im X = X V denotes the image of X and ker X is its kernel. Moreover, X −1 T stands for the inverse image of T ⊂ W . The special subspaces Im B and ker C are denoted by B, and K , respectively. The zero dimension subspace is indicated as 0 and σ {A} denotes the spectrum of the linear transformation A. The identity operator is denoted by I: Ix = x; A 0 is the identity operator, for any given linear transformation A. The matrix of a given linear transformation A : X → X in a given basis is noted as A ∈ R n×n . Additionally, for the elements v, w, . . . ∈

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In this paper, we show in detail a synthesis procedure of the control scheme recently proposed in [3]. This control scheme has the advantage of combining the classical linear control techniques with the sophisticated robust control techniques. This control scheme is specially ad hoc for unmanned aircraft vehicles, where it is important not only to reject the actual nonlinearities and the unexpected changes of the structure, but also to look for the simplicity and effectiveness of the control scheme.

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International audienceThis paper considers the problem of stabilizing a single-input single-output linear time varying system using a low order controller and a reference model. The closed loop is a linear singularly perturbed system with uniform asymptotic stability behavior. We calculate bounds as in Kokotovi'c's book, such that the uniform asymptotic stability of the singularly perturbed system is guaranteed. We show how to design a control law such that the system dynamics is assigned by a Hurwitz polynomial with constant coefficients

International audienceIn this paper, we give an explicit solution to the behavioral reachability problem for linear time invariant systems, which amounts to finding an explicit control law that reaches a given final input-state pair (u1, x 1) in a given finite time t1. We first tackle the case of state space realizations, and we then extend the obtained results to the case of implicit realizations. For this, we use the geometric approach and some results of the viability theory. Some complements are given about the existing relationships between reachability and pole placement, as well as some notions of unicity and existence of solution

Over the past few decades, there has been growing support for the idea that cancer needs an interdisciplinary approach. Therefore, the international cancer community has developed several strategies as outlined in the WHO non-communicable diseases Action Plan (which includes cancer control) as the World Health Assembly and the UICC World Cancer Declaration, which both include primary prevention, early diagnosis, treatment, and palliative care. This paper highlights experiences/ideas in cancer control for international collaborations between low, middle, and high income countries, including collaborations between the European Union (EU) and African Union (AU) Member States, the Latin-American and Caribbean countries, and the Eastern Mediterranean countries. These proposals are presented within the context of the global vision on cancer control set forth by WHO in partnership with the International Union Against Cancer (UICC), in addition to issues that should be considered for collaborations at the global level: cancer survival (similar to the project CONCORD), cancer control for youth and adaptation of Clinical Practice Guidelines. Since cancer control is given lower priority on the health agenda of low and middle income countries and is less represented in global health efforts in those countries, EU and AU cancer stakeholders are working to put cancer control on the agenda of the EU-AU treaty for collaborations, and are proposing to consider palliative care, population-based cancer registration, and training and education focusing on primary prevention as core tools. A Community of Practice, such as the Third International Cancer Control Congress (ICCC-3), is an ideal place to share new proposals, learn from other experiences, and formulate new ideas. The aim of the ICCC-3 is to foster new international collaborations to promote cancer control actions in low and middle income countries. The development of supranational collaborations has been hindered by the fact that cancer control is not part of the objectives of the Millennium Development Goals (MGGs). As a consequence, less resources of development aids are allocated to control NCDs including cancer.