The mathematical model of the dynamics of the groundwater level in the area between the drains during the regulation of the pressure in the drains is developed. This model is proposed for the regulation of the water r...
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The 'digital twin' technology fits well into the ideology of building intelligent fault-tolerant controlsystems. The technology is based on the premise that for each system it is possible to create a represen...
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This paper highlights the importance of using a Doubly-Fed Induction Generators (DFIG) in the wind industry due to their ability to adapting for all variations in wind speed, thus providing increased efficiency and re...
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Accurate control of robots at high speeds requires a control system that can take into account the kinodynamic interactions of the robot with the environment. Prior works on learning inverse kinodynamic (IKD) models o...
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ISBN:
(数字)9781665479271
ISBN:
(纸本)9781665479271
Accurate control of robots at high speeds requires a control system that can take into account the kinodynamic interactions of the robot with the environment. Prior works on learning inverse kinodynamic (IKD) models of robots have shown success in capturing the complex kinodynamic effects. However, the types of controlproblems these approaches can be applied to are limited only to that of following pre-computed kinodynamically feasible trajectories. In this paper we present Optim-FKD, a new formulation for accurate, high-speed robot control that makes use of a learned forward kinodynamic (FKD) model and non-linear least squares optimization. Optim-FKD can be used for accurate, high speed control on any control task specifiable by a non-linear least squares objective. Optim-FKD can solve for control objectives such as path following and time-optimal control in real time, without needing access to pre-computed kinodynamically feasible trajectories. We empirically demonstrate these abilities of our approach through experiments on a scale one-tenth autonomous car. Our results show that Optim-FKD can follow desired trajectories more accurately and can find better solutions to optimal controlproblems than baseline approaches.
To improve the stability requirements of power systems with high renewable energy penetration, more and more converters adopt Virtual synchronous generator (VSG) control strategies. Especially, the independent islande...
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PID control is an excellent control method and one of the first inverter control strategies to emerge. Its robustness, precise control and simple algorithm logic are often used in industrial production technology to c...
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The proceedings contain 103 papers. The topics discussed include: flexible activation bag: learning activation functions in autoencoder networks;effects of wind noise on hybrid active noise cancellation headphones;ana...
ISBN:
(纸本)9798350336504
The proceedings contain 103 papers. The topics discussed include: flexible activation bag: learning activation functions in autoencoder networks;effects of wind noise on hybrid active noise cancellation headphones;analytical modelling of a hybrid reluctance motor based on magnetic equivalent circuit;reinforcement learning of LQR control policy by a double inverted-pendulum biomechanical model;a data-driven hybrid automaton framework to modelingcomplex dynamical systems;enhanced power-sharing control algorithm for dual-inverter-fed open-end-winding induction motor in hybrid electric vehicles;a python framework for system-on-chip power integrity simulation;smart highways based vehicle speed sensor with piezoelectric energy harvesting: a progress report;a deep multi-modal cyber-attack detection in industrial controlsystems;performance improvement of flexible common ground flying capacitor PV inverter using model predictive control;guaranteed quantization error computation for neural network model compression;and reconfigurable LNA with on-line fine-tuning of linearity and gain for 5G industrial communications applications.
Many problems associated with optimization, optimal management and numerical calculations have been investigated and solved for problems with free boundaries. This paper is devoted to the study of the problem with fre...
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In recent years, with the development of cloud computing and Internet of Things technology, earthquake observation technology has made tremendous *** earthquake agency developed a low-cost local magnetic field observa...
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ISBN:
(纸本)9798350389913;9798350389906
In recent years, with the development of cloud computing and Internet of Things technology, earthquake observation technology has made tremendous *** earthquake agency developed a low-cost local magnetic field observation system based on cloud architecture to carry high-density deployed sensors. With the increasing deployment of sensors and the richness of application scenarios, existing access control models couldn't meet the needs of actual business *** original access control technology was based on physical network security protocols and IoT device security *** it could eliminate some security risks during the access process, there were still shortcomings that couldn't be well adapted to the needs of large-scale IoT device deployment ***, using complex access control models may result in neglecting the low local computing power of IoT geomagnetic field observation *** order to solve the above problems, the project team conducted research and analysis on access control between geomagnetic observation devices based on fog computing and combined with blockchain *** IoT access control model suitable for geomagnetic observation network systems was designed based on research *** model uses fog node agents to place the main work on the blockchain for completion and solve the problem of low computing power in some IoT *** smart contracts, the model has achieved control over device access permissions,it provided an effective and secure method for IoT access control.
In recent years, quantum information systems have attracted increasing attention of researchers in the field of computer science and physics. However, the introduction and practical application of quantum computing is...
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