Examinando por Materia "INVARIANCIA"
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- Artículo de Publicación PeriódicaAn extension of LaSalle’s invariance principle for switched systems(2006) Mancilla-Aguilar, J. L.; García Galiñanes, Rafael"This paper addresses invariance principles for a certain class of switched nonlinear systems. We provide an extension of LaSalle’s Invariance Principle for these systems and state asymptotic stability criteria. We also present some related results that deal with the compactness of the trajectories of these switched systems and that are interesting by their own."
- Ponencia en CongresoFrom operational to declarative specifications using a genetic algorithm(2018-05) Molina, Facundo; Degiovanni, Renzo; Regis, Germán; Castro, Pablo; Aguirre, Nazareno; Frías, Marcelo"In specification-based test generation, sometimes having a formal specification is not sufficient, since the specification may be in a different formalism from that required by the generation approach being used. In this paper, we deal with this problem specifically in the context in which, while having a formal specification in the form of an operational invariant written in a sequential programming language, one needs, for test generation, a declarative invariant in a logical formalism. We propose a genetic algorithm that given a catalog of common properties of invariants, such as acyclicity, sortedness and balance, attempts to evolve a conjunction of these that most accurately approximates an original operational specification. We present some details of the algorithm, and an experimental evaluation based on a benchmark of data structures, for which we evolve declarative logical invariants from operational ones."
- Ponencia en CongresoInvariance results for constrained switched systems(2010) Mancilla-Aguilar, J. L.; García Galiñanes, Rafael"In this paper we address invariance principles for nonlinear switched systems with otherwise arbitrary compact index set and with constrained switchings. We present an extension of LaSalle's invariance principle for these systems and derive by using detectability notions some convergence and asymptotic stability criteria. These results enable to take into account in the analysis of stability not only state-dependent constraints but also to treat the case in which the switching logic has memory, i.e., the active subsystem only can switch to a prescribed subset of subsystems."
- Artículo de Publicación PeriódicaISS implies iISS even for switched and time-varying systems (if you are careful enough)(2019-06) Haimovich, Hernán; Mancilla-Aguilar, J. L."For time-invariant systems, the property of input-to-state stability (ISS) is known to be strictly stronger than integral-ISS (iISS). Known proofs of the fact that ISS implies iISS employ Lyapunov characterizations of both properties. For time-varying and switched systems, such Lyapunov characterizations may not exist, and hence establishing the exact relationship between ISS and iISS remained an open problem, until now. In this paper, we solve this problem by providing a direct proof, i.e. without requiring Lyapunov characterizations, of the fact that ISS implies iISS, in a very general time-varying and switched-system context. In addition, we show how to construct suitable iISS gains based on the comparison functions that characterize the ISS property, and on bounds on the function f defining the system dynamics. When particularized to time-invariant systems, our assumptions are even weaker than existing ones. Another contribution is to show that for time-varying systems, local Lipschitz continuity of f in all variables is not sufficient to guarantee that ISS implies iISS. We illustrate application of our results on an example that does not admit an iISS-Lyapunov function."
- Artículo de Publicación PeriódicaOn zero-input stability inheritance for time-varying systems with decaying-to-zero input power(2017-06) Mancilla-Aguilar, J. L.; Haimovich, Hernán"Stability results for time-varying systems with inputs are relatively scarce, as opposed to the abundant literature available for time-invariant systems. This paper extends to time-varying systems existing results that ensure that if the input converges to zero in some specific sense, then the state trajectory will inherit stability properties from the corresponding zero-input system. This extension is non-trivial, in the sense that the proof technique is completely novel, and allows to recover the existing results under weaker assumptions in a unifying way."
- Ponencia en CongresoSome invariance principles for constrained switched systems(2010) Mancilla-Aguilar, J. L.; García Galiñanes, Rafael"In this paper we consider switched nonlinear systems under average dwell time switching signals, with an otherwise arbitrary compact index set and with additional constraints in the switchings. We present invariance principles for these systems and derive by using observability-like notions some convergence and asymptotic stability criteria. These results may enable us to analyze the stability of solutions of switched systems with both state-dependent constrained switching and switching whose logic has memory, i.e., the active subsystem only can switch to a prescribed subset of subsystems."
- Ponencia en CongresoTraining binary classifiers as data structure invariants(2019-05) Molina, Facundo; Degiovanni, Renzo; Ponzio, Pablo; Regis, Germán; Aguirre, Nazareno; Frías, Marcelo"We present a technique to distinguish valid from invalid data structure objects. The technique is based on building an artificial neural network, more precisely a binary classifier, and training it to identify valid and invalid instances of a data structure. The obtained classifier can then be used in place of the data structure’s invariant, in order to attempt to identify (in)correct behaviors in programs manipulating the structure. In order to produce the valid objects to train the network, an assumed-correct set of object building routines is randomly executed. Invalid instances are produced by generating values for object fields that “break” the collected valid values, i.e., that assign values to object fields that have not been observed as feasible in the assumed-correct executions that led to the collected valid instances. We experimentally assess this approach, over a benchmark of data structures.We show that this learning technique produces classifiers that achieve significantly better accuracy in classifying valid/invalid objects compared to a technique for dynamic invariant detection, and leads to improved bug finding."