The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having l...
详细信息
This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equatio...
详细信息
This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equatio...
详细信息
ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equations (PDEs) through the boundaries. First, a Lyapunov result characterizing the ISS property for finite-dimensional systems is extended to deal with coupled ODE and PDE systems. The proposed ISS condition is then applied to derive stability and stabilization conditions in terms of linear matrix inequality constraints assuming magnitude bounded disturbances at the boundaries. Two convex optimization problems are also proposed in order to obtain either an optimized reachable set estimate or a boundary controller that minimizes the disturbance effects on the ${\mathcal{L}}_{2} \times \mathbb{R}$-norm of the system states. Numerical examples illustrate the potential of the proposed approach.
A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase...
A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.
This article presents the mathematical model of a 2 KW DBI (Dual Buck Inverter) converter that can be used in renewable energy applications. The inverter operating modes are described with the equations that model the...
详细信息
The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having l...
详细信息
ISBN:
(数字)9798350373011
ISBN:
(纸本)9798350373028
The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms.
In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor d...
In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.
The development of interoperability is more and more an essential task for all kinds of organizations. It needs to be measured, verified, and continuously improved. With the advent of the Internet of Things, Industry ...
详细信息
The Internet of Things (IoT) devices have been identified to have low security measures by default, thus making them highly vulnerable to malicious attacks. Machine learning-based intrusion detection systems (IDS) are...
详细信息
ISBN:
(数字)9798350362510
ISBN:
(纸本)9798350362527
The Internet of Things (IoT) devices have been identified to have low security measures by default, thus making them highly vulnerable to malicious attacks. Machine learning-based intrusion detection systems (IDS) are used to mitigate these attacks, however, there is a compromise in security and privacy of data ownership between IoT devices. This paper proposes a Federated Ensemble IDS (CNN-GRU and LSTM-GRU) for monitoring IoT network activities using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM) networks that classifies the network as either normal or malicious. Two aggregation functions, including wFedAvg and wFedProx, are developed to create a global model from different clients’ contribution. We perform an evaluation of the proposed IDS on CICIoT2023 and FLNET2023 datasets. The results show that with wFedAvg, the CNN-GRU achieved an accuracy of 98.25% and 99.25% on the CICIoT2023 and FLNET2023 datasets respectively. Additionally, the LSTM-GRU model shows a detection accuracy of 93.36% and 95.66%, respectively on CICIoT2023 and FLNET2023 datasets. The performance shows that the proposed method is robust enough to enhancing the privacy of IoT devices.
This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent dis...
This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent disturbances. Firstly, the robust controller is designed to ensure that the closed-loop system is Input-to-State Stable (ISS) with a guaranteed stability region regardless of the ESN control action and exogenous disturbances. Then, the ESN-based controller is trained in order to mitigate the effects of disturbances on the system output. A numerical example demonstrates the potential of the proposed control design method.
暂无评论