Academic literature on the topic 'DES identification'

Krista Ratcliffe’s term “non-identification” offers a version of identification that assumes identity is not always identifiable. As an attitude that fosters cross-cultural listening, non-identification asks us to listen to others from a place of “neutrality,” with “hesitancy,” “humility,” and “pause” in order to consider identity’s fluid nature (73). This thesis first argues that this term might also describe speaking strategies premised on non-identifiability. As I’ll show, an inventive non-identification would articulate some rhetorical strategies that neither “identification” nor “disidentification” currently articulate. However, rhetorical scholars need more theoretical and practical guidance for what this kind of speech looks like. So, this thesis also argues why, despite criticism to the contrary, the writing of Kenneth Burke offers an ideal account for inventive non-identification. Burke’s descriptions of the terms “synecdoche function,” the “mystic” and “poetic language” achieve the same effects as Ratcliffe’s non-identification, yet Burke describes these same effects from the perspective of the speaker. Following my re-reading of Burke, I ground the theory of inventive non-identification in a brief rhetorical analysis of Yan Phou Lee’s 1887 autobiography When I Was a Boy in China. By showing how this theory applies to Asian American rhetoric, I conclude that inventive non-identification has utility for the field of rhetoric more broadly.

In modern manufacturing, industrial robots are essential components that allow saving cost, increase quality and productivity for instance. To achieve such goals, high accuracy and speed are simultaneously required. The design of control laws compliant with such requirements demands high-fidelity mathematical models of those robots. For this purpose, dynamic models are built from experimental data. The main objective of this thesis is thus to provide robotic engineers with automatic tools for identifying dynamic models of industrial robot arms. To achieve this aim, a comparative analysis of the existing methods dealing with robot identification is made. That allows discerning the advantages and the limitations of each method. From those observations, contributions are presented on three axes. First, the study focuses on the estimation of the joint velocities and accelerations from the measured position, which is required for the model construction. The usual method is based on a home-made prefiltering process that needs a reliable knowledge of the system’s bandwidths, whereas the system is still unknown. To overcome this dilemma, we propose a method able to estimate the joint derivatives automatically, without any setting from the user. The second axis is dedicated to the identification of the controller. For the vast majority of the method its knowledge is indeed required. Unfortunately, for copyright reasons, that is not always available to the user. To deal with this issue, two methods are suggested. Their basic philosophy is to identify the control law in a first step before identifying the dynamic model of the robot in a second one. The first method consists in identifying the control law in a parametric way, whereas the second one relies on a non-parametric identification. Finally, the third axis deals with the home-made setting of the decimate filter. The identification of the noise filter is introduced similarly to methods developed in the system identification community. This allows estimating automatically the dynamic parameters with low covariance and it brings some information about the noise circulation through the closed-loop system. All the proposed methodologies are validated on an industrial robot with 6 degrees of freedom. Perspectives are outlined for future developments on robotic systems identification and other complex problems.