Search results for "rame"
showing 10 items of 18055 documents
Colorimetic biosensing dispositive based on reagentless hybrid biocomposite: Application to hydrogen peroxide determination
2016
Abstract An efficient approach to enhance the performance of colorimetric biosensors has been developed. The biosensor is based on the co-immobilization of the reagent 3,3′,5,5′-teramethylbencidine (TMB) and the enzyme horseradish peroxidase (HRP) in a PDMS-TEOS-SiO2NPs support. The HRP, in presence of H2O2, catalyzes the oxidation of TMB, producing a blue color. The generated biosensor, doped with the substrate (TMB) and the enzyme (HRP) (entrapped or adsorbed), has been used to determine H2O2 in real samples. Firstly, the immobilization of TMB and HRP in the composite has been studied in order to find the best suitable configuration. The kinetic parameters Vmax (maximum reaction rate) and…
Towards a simulation-based tuning of motion cueing algorithms
2016
Abstract This paper deals with the problem of finding the best values for the parameters of Motion Cueing Algorithms (MCA). MCA are responsible for controlling the movements of robotic motion platforms used to generate the gravito-inertial cues of vehicle simulators. The values of their multiple parameters, or coefficients, are hard to establish and they dramatically change the behaviour of MCA. The problem has been traditionally addressed in a subjective, partially non-systematic, iterative, time-consuming way, by seeking pilot/driver feedback on the generated motion cues. The aim of this paper is to introduce a different approach to solve the problem of MCA tuning, by making use of a simu…
A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical …
2020
In the present paper, for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a decision criterion and averaging this criterion over pivots’ probability distributions is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging via pivotal quantities (ISE&APQ) is independent of the choice of priors and represents a novelty i…
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Convergence of direct recursive algorithm for identification of Preisach hysteresis model with stochastic input
2015
We consider a recursive iterative algorithm for identification of parameters of the Preisach model, one of the most commonly used models of hysteretic input-output relationships. The classical identification algorithm due to Mayergoyz defines explicitly a series of test inputs that allow one to find parameters of the Preisach model with any desired precision provided that (a) such input time series can be implemented and applied; and, (b) the corresponding output data can be accurately measured and recorded. Recursive iterative identification schemes suitable for a number of engineering applications have been recently proposed as an alternative to the classical algorithm. These recursive sc…
Adaptive Asymptotically Tracking Control for Uncertain Strict-Feedback Nonlinear Systems with Input Quantization
2018
In this paper, we investigate the output tracking control problem for a class of uncertain nonlinear systems in parametric strict feedback form with quantized input. A novel backstepping based adaptive quantized control scheme is proposed. Different from the existing results, the true quantization parameters are allowed to be unknown in the design of adaptive controller. It is shown that with the proposed control scheme, the system output can track the desired trajectory asymptotically and all the closed-loop signals are globally uniformly bounded.
Adaptive Backstepping Control of a 2-DOF Helicopter
2019
This paper proposes an adaptive nonlinear controller for a 2-Degree of Freedom (DOF) helicopter. The proposed controller is designed using backstepping control technique and is used to track the pitch and yaw position references independently. A MIMO nonlinear mathematical model is derived for the 2DOF helicopter based on Euler-Lagrange equations, where the system parameters and the control coefficients are uncertain. Unlike some existing control schemes for the helicopter control, the developed controller does not require the knowledge on the system uncertain parameters. Updating laws are used to estimate the unknown parameters. It is shown that not only the global stability is guaranteed …
Distributed Adaptive Consensus Tracking Control of Uncertain High-order Nonlinear Systems under Directed Graph Condition
2018
In this paper, we investigate the output consensus tracking problem for a class of high-order nonlinear systems subjected to unknown parameters and uncertain external disturbances. A novel backstepping based distributed adaptive control scheme is presented under the directed communication status. For the subsystems without direct access to time-varying desired trajectory, local estimators are introduced and the corresponding adaptive laws are designed in a totally distributed fashion. With the presented scheme, the assumption on linearly parameterized reference signal and the information exchange operation of subsystem inputs in the existing results are no longer needed. It is shown that al…
Analysis of hybrid vehicle transmissions with any number of modes and planetary gearing: kinematics, power flows, mechanical power losses
2021
Abstract This paper is focused on upgrading a unified parametric model, available in the literature, that can perform both the analysis and the design of Power-Split Continuously Variable Transmissions (PS-CVTs), which are particularly promising to deploy in the hybrid electric powertrain. In particular, this work is focused on the analysis of PS-CVTs and proposes a new matrix approach for identifying the basic functional parameters underlying the model from the constructive layout of the transmission. This new method does not rely on a case-specific formulation, thus befits any power-split transmission, regardless of the number of planetary and ordinary gear sets and their constructive arr…
Distributed adaptive leader–follower and leaderless consensus control of a class of strict-feedback nonlinear systems : a unified approach
2020
In this paper, distributed adaptive consensus for a class of strict-feedback nonlinear systems under directed topology condition is investigated. Both leader–follower and leaderless cases are considered in a unified framework. To design distributed controller for each subsystem, a local compensatory variable is generated based on the signals collected from its neighbors. Such a technique enables us to solve the leader–follower consensus and leaderless consensus problems in a unified framework. And it further allows us to treat the leaderless consensus as a special case of the leader–follower consensus. For leader–follower consensus, the assumption that the leader trajectory is linearly para…