Search results for "Machine"
showing 10 items of 2592 documents
Online Estimation of the Mechanical Parameters of an Induction Machine Using Speed Loop characteristics and Recursive Least Square Technique
2022
This paper presents a novel approach for estimation of mechanical parameters, inertia and friction coefficient of an Induction Machine (IM) using speed loop characteristics and Recursive Least Square (RLS) estimator. Using the 5th order dynamic equation for Induction Machine and the forgetting factor based RLS algorithm the technique herein proposed employs the speed of the machine and the torque as the inputs for the estimator. Results obtained compares the estimated parameters with the actual parameters under multiple step varying and exponentially varying scenarios. Upon analyzing the results, the validity and the effectiveness of the proposed identification technique is confirmed
Enhancing Speed Loop PI Controllers with Adaptive Feed-forward Neural Networks: Application to Induction Motor Drives
2022
This paper proposes the idea to improve the performance of the speed loop PI controller by using feed-forward and adaptive control actions. Indeed, when the system to be controlled is required to track a rapidly changing reference frame, higher bandwidth is usually required, making the system more sensitive to noise and consequently less robust. In such cases, to achieve a better performance in reference tracking while keeping noise rejection capacity, one idea is to use a feed-forward controller, employed to enhance the required tracking, leaving the feedback action to stabilize the system and suppress higher frequency disturbance. As such, this paper analysis the classical PI based field …
Towards safe reinforcement-learning in industrial grid-warehousing
2020
Abstract Reinforcement learning has shown to be profoundly successful at learning optimal policies for simulated environments using distributed training with extensive compute capacity. Model-free reinforcement learning uses the notion of trial and error, where the error is a vital part of learning the agent to behave optimally. In mission-critical, real-world environments, there is little tolerance for failure and can cause damaging effects on humans and equipment. In these environments, current state-of-the-art reinforcement learning approaches are not sufficient to learn optimal control policies safely. On the other hand, model-based reinforcement learning tries to encode environment tra…
Learned Sorted Table Search and Static Indexes in Small-Space Data Models
2023
Machine-learning techniques, properly combined with data structures, have resulted in Learned Static Indexes, innovative and powerful tools that speed up Binary Searches with the use of additional space with respect to the table being searched into. Such space is devoted to the machine-learning models. Although in their infancy, these are methodologically and practically important, due to the pervasiveness of Sorted Table Search procedures. In modern applications, model space is a key factor, and a major open question concerning this area is to assess to what extent one can enjoy the speeding up of Binary Searches achieved by Learned Indexes while using constant or nearly constant-space mod…
Some Experiments in Supervised Pattern Recognition with Incomplete Training Samples
2002
This paper presents some ideas about automatic procedures to implement a system with the capability of detecting patterns arising from classes not represented in the training sample. The procedure aims at incorporating automatically to the training sample the necessary information about the new class for correctly recognizing patterns from this class in future classification tasks. The Nearest Neighbor rule is employed as the central classifier and several techniques are added to cope with the peril of incorporating noisy data to the training sample. Experimental results with real data confirm the benefits of the proposed procedure.
The Evolution of Blockchain Virtual Machine Architecture Towards an Enterprise Usage Perspective
2019
Virtualization in the context of blockchain systems represents an essential phase in the development and migration of services from public chains to enterprise logic. Most of the ongoing blockchain uses-cases are using the existing public ledgers, but for business products and services, there is a need for custom tailored solutions to ensure flexibility and security. The Ethereum Virtual Machine has opened new ways to solve problems that require a public proof by executing logic on a decentralized ecosystem. In a natural evolutive process, virtualization logic was shaped by numerous architectures and business requirements. Beside performance and scalability, enterprise virtual machines are …
Towards Efficient Teacher Assisted Assignment Marking Using Ranking Metrics
2017
This paper describes a tool with supporting methodology for efficient teacher assisted marking of open assignments based on student answer ranking metrics. It includes a methodology for how to design tasks for markability. This improves marking efficienty and reduces cognitive strain for the teacher during marking, and also allows for easily giving feedback to students on common pitfalls and misconceptions to improve both the learning outcome for the students as well as the teacher’s productivity by reducing the time needed for marking open assignments. An advantage with the method is that it is language agnostic as well as generally being agnostic to the discipline of the course being asse…
Ontology-Guided Approach to Feature-Based Opinion Mining
2011
The boom of the Social Web has had a tremendous impact on a number of different research topics. In particular, the possibility to extract various kinds of added-value, informational elements from users' opinions has attracted researchers from the information retrieval and computational linguistics fields. However, current approaches to socalled opinion mining suffer from a series of drawbacks. In this paper we propose an innovative methodology for opinion mining that brings together traditional natural language processing techniques with sentimental analysis processes and Semantic Web technologies. The main goals of this methodology is to improve feature-based opinion mining by employing o…
Comparing Translation and Post-editing: An Annotation Schema for Activity Units
2016
The current chapter introduces an annotation schema of TPR data that categorises post-editing behaviour into five different classes and compares general-language and domain-specific English-to-German translation and post-editing with respect to production times, key-logging (text production activity and text elimination activity) and eye-tracking data (total reading times on source text and on target text). The results support the hypothesis that post-editing is faster than translation from scratch for both domain-specific and non-domain-specific text types. When key-logging and eye-tracking data are taken into consideration, domain-specific texts require more effort when translating from s…
Learning high-level manipulative tasks through imitation
2006
This paper presents ConSCIS, Conceptual Space based Cognitive Imitation System, which tightly links low-level data processing with knowledge representation in the context of robot imitation. Our focus is on the program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a two dimensional world populated with various objects in which observation/imitation takes place. To validate our appr…