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Articles 1 - 7 of 7
Full-Text Articles in Controls and Control Theory
Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede
Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede
Doctoral Dissertations
The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt
All Dissertations
Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …
Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla
Optimal And Robust Control Problems Of Microalgae Cultivation, Mariana Rodriguez-Jara, Luis A. Ricardez-Sandoval, Carlos E. Ramirez-Castelan, Hector Puebla
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
The Algorithm For The Design Of Fine Granular Substances’ Smart-Type Heat And Moisture Converters Based On Their Accuracy And Speed Criteria, Erkin Uljaev, Ali Abduakhatovich Abduraxmanov
The Algorithm For The Design Of Fine Granular Substances’ Smart-Type Heat And Moisture Converters Based On Their Accuracy And Speed Criteria, Erkin Uljaev, Ali Abduakhatovich Abduraxmanov
Chemical Technology, Control and Management
The paper describes a technique and algorithm allowing to perform parametric design of smart-type heat and moisture converters (hereinafter SHMC) of fine-grained dispersive materials based on their criteria of accuracy and speed. The proposed algorithm optimizes the process of design of smart-type switches and ensure optimal performance of the switches. The method of calculation and selection of optimal parameters of smart-type heat and moisture converters intended to be used in the measurement of parameters such as heat and humidity of fine dispersive substances are aimed at boosting two parameters, i.e., the accuracy and speed. Also, the design stages have been …
Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang
Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang
Electronic Theses and Dissertations
Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large …
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)
Library Philosophy and Practice (e-journal)
Abstract
Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Publications
In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …