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Exponential Continuous Non-Parametric Neural Identifier With Predefined Convergence Velocity

IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1049-1060页

作者： Mariana Ballesteros Rita Q.Fuentes-Aguilar isaac chairez Instituto Politécnico Nacional Centro de Innovación y Desarrollo Tecnológico en Cómputo Unidad Profesional Interdisciplinaria de Biotecnología 07340Mexico CityMexico Tecnológico de Monterrey School of Engineering and SciencesZapopanJalisco 45138Mexico Department of Bioprocesses UPIBIInstituto Politécnico Nacional07340Mexico City

This paper addresses the design of an exponential function-based learning law for artificial neural networks(ANNs)with continuous *** ANN structure is used to obtain a non-parametric model of systems with uncertainties,which are described by a set of nonlinear ordinary differential *** novel adaptive algorithms with predefined exponential convergence rate adjust the weights of the *** first algorithm includes an adaptive gain depending on the identification error which accelerated the convergence of the weights and promotes a faster convergence between the states of the uncertain system and the trajectories of the neural *** second approach uses a time-dependent sigmoidal gain that forces the convergence of the identification error to an invariant set characterized by an *** generalized volume of this ellipsoid depends on the upper bounds of uncertainties,perturbations and modeling *** application of the invariant ellipsoid method yields to obtain an algorithm to reduce the volume of the convergence region for the identification *** adaptive algorithms are derived from the application of a non-standard exponential dependent function and an associated controlled Lyapunov *** examples demonstrate the improvements enforced by the algorithms introduced in this study by comparing the convergence settings concerning classical schemes with non-exponential continuous learning *** proposed identifiers overcome the results of the classical identifier achieving a faster convergence to an invariant set of smaller dimensions.

关键词： Exponential Lyapunov functions learning laws non-parametric identifier predefined convergence rate

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Output Second-order Sliding-mode Control for a Gecko Biomimetic Climbing Robot

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Journal of Bionic Engineering 2019年第4期16卷 633-646页

作者： David Cruz-Ortiz Mariana Ballesteros-Escamilla isaac chairez Alberto Luviano SEPl UPIITAInstitute Politecnico NationalAv.Institute Politecnico National 258007340Mexico Bioprocesses Department UPIBIInstitute Politecnico NationalAv.Acueducto 55007340Mexico

The aim of this study is to propose the output controller to solve the execution of the gait sequence for Gecko Bio-inspired Robotic Devices (GBRDs).The Twisting Controller (TC) serves as basis of the tracking trajectory designed *** TC uses both the tracking error and its estimated derivative,which is calculated by a set of distributed Super-Twisting Algorithms (STAs).Each STA is implemented as a robust and exact *** output-based controller structure corresponds to a sort of decentralized form for robotic ***,each articulation is controlled by an independent TC.A set of proposed references trajectories reproduce the gait cycle of a Real Gecko-Lizard (RG-L).The reference trajectories are proposed as the superposition of sigmoid functions ful-filling the conditions of the Bezzier *** simulations evaluate the GBRD movement enforced by the suggested controller in the horizontal as well as the vertical *** own 3D printed GBRD is the experimental platform aimed to test the distributed *** controlled vacuum pumps are used to adhere the GBRD to the wall surfaces.A set of experimental validations confirm the robustness and the reliability of the proposed controller when its performance is compared with classical output feedback controllers.

关键词： gecko robot biomimetic output-based controller twisting controller Super-Twisting Algorithm(STA)

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Coliforms and Helminth Eggs Removals by Coagulation-Flocculation Treatment Based on Natural Polymers

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Journal of Water Resource and Protection 2013年第11期5卷 1027-1036页

作者： Evelyn Zamudio-Pérez Neftalí Rojas-Valencia isaac chairez Luis Gilberto Torres Bioprocesess Department UPIBI-Instituto Politécnico Nacional Barrio la Laguna Ticomán Mexico Engineering Institute UNAM Environmental Engineering Department Coyoacán Mexico

Wastewater from a municipal wastewater treatment plant (Mexico) was treated by a coagulation-flocculation using natural gums. The residual water was characterized in terms of organic load, and biological contaminants, i.e. total Coliforms (TC), fecal Coliforms (FC) and helminth eggs (HE). The sample has values of 2.8 × 107 MPN/100 ml, 8.48 × 106 MPN/100 ml and 470 HE/L is regarded to TC, FC and HH, respectively. The HE identified in the wastewaters were Diphyllobothrium latum, Ascaris lumbricoides, Hymenolepis nana and Toxocara canis. From several gums, Hydroxypropyl triammonium chloride guar gum (HPTAC-guar) was selected as the most adequate coagulant-flocculant for the class of municipal wastewater (MWW). A diminution of 82% for TC, 94% for FC and 99% for HE was obtained. Besides, the reduction of chemical oxygen demand (COD) and turbidity removals were 46% and 39% respectively. The natural gum mixed with Ca(OH)2, obtained removals of 52% for TC, 100% for HE, 47% for COD and 30% for turbidity.

关键词： Coagulation Fecal Coliforms Flocculation Helminth Eggs Total Coliforms Wastewaters

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