We present transport measurements of a tunable silicon metal-oxide-semiconductor double quantum dot device with lateral geometry. Experimentally extracted gate-to-dot capacitances show that the device is largely symmetric under the gate voltages applied. Intriguingly, these gate voltages themselves are not symmetric. Comparison with numerical simulations indicates that the applied gate voltages serve to offset an intrinsic asymmetry in the physical device. We also show a transition from a large single dot to two well isolated coupled dots, where the central gate of the device is used to controllably tune the interdot coupling.
In this study a Neural Network based fault tolerant control is proposed to accommodate oil leakages in a magnetorheological suspension system based in a half car dynamic model. This model consists of vehicle body (spring mass) connected by the MR suspension system to two lateral wheels (unsprung mass). The semi-active suspension system is a four states nonlinear model; it can be written as a state space representation. The main objectives of a suspension are: Isolate the chassis from road disturbances (passenger comfort) and maintain contact between tire and road to provide better maneuverability, safety and performance. On the other hand, component faults/failures are inevitable in all practical systems, the shock absorbers of semi-active suspensions are prone to fail due to fluid leakage but quickly detect and diagnose this fault in the system, avoid major damage to the system and ensure the safety of the driver. To successfully achieve desirable control performance, it is necessary to have a damping force model which can accurately represent the highly nonlinear and hysteretic dynamic of the MR damper. To simulate parameters of the damper, a quasi-static model was applied, quasi-static approaches are based on non-newtonian yield stress fluids flow by using the Bingham MR Damper Model, relating the relative displacement of the piston, the frictional force, a damping constant, the stiffness of the elastic element of the damper and an offset force. The Fault detection and isolation module is based on residual generation algorithms. The residua r is computed as the difference between the displacement signal of functional and faulty model, when the residual is close to zero, the process is free of faults, while any change in r represents a faulty scheme then a wavelet transform, (Morlet wave function) is used to determine the natural frequencies and amplitudes of displacement and acceleration signal during the failure, this module provides parameters to the neural network controller in order to accommodate the failure using compensation forces from the remaining healthy damper. The neural network uses the error between the plant output and the neural network plant for computing the required electric current to correct the malfunction using the inverse dynamics function of the MR damper model. Consequently, a bump condition, and a random profile road (ISO 8608) described by the power spectral density (PSD) of its vertical displacement, is used as disturbance of control system. The performance of the proposed FTC structure is demonstrated trough simulation. Results shows that the control system could reduce the effect of the partial fault of the MR Damper on system performance.
Quantum dot (QD) lay-outs are becoming more complex as the technology is being applied to more complex multi-QD structures. This increase in complexity requires improved capacitance modeling both for design and accurate interpretation of , is demonstrated for both structures when the details of the structure are transferred from the CAD to the model capturing the full 3D topography. Small uncertainty in device dimensions due to uncontrolled variation in processing, like layer thickness and gate size, are calculated to be sufficient to explain the disagreement. The sensitivity of the capacitances to small variations in the structure also highlights the limits of accuracy of capacitance models for QD analysis. We furthermore observe that a critical density, the metal insulator transition, 1 can be used as a good approximation of the metallic edge of the quantum dot when electron density in the dot is calculated directly with a semiclassical simulation.2
Los robots paralelos son utilizados en diversas áreas como la simulación de movimiento, la medicina y la manufactura, entre otras. Se han diseñado y construido numerosos de ellos teniendo en cuenta aspectos como grados de libertad, modelos matemáticos que aproximan la dinámica real del sistema donde actúan, y las estrategias de control para que respondan adecuadamente ante perturbaciones. El presente artículo describe las generalidades de robots paralelos con el fin de dar a conocer sus aplicaciones industriales, arquitecturas y notación, métodos y representaciones matemáticas necesarias para el análisis de su movilidad, el cálculo de la cinemática y la dinámica presentes, el estudio del espacio de trabajo, así como las estrategias de control implementadas. Se describen las investigaciones y desarrollos futuros que pueden realizarse en esta área de la robótica, así como una amplia revisión bibliográfica que permite al lector incursionar profundamente en cualquier aspecto que le sea de interés.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.