This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear *** asymmetric output constraints and input saturation are *** asymmetric barr...
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This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear *** asymmetric output constraints and input saturation are *** asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints.A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear *** avoid the"explosion of complexity",the dynamic surface control(DSC)technique is employed to filter the virtual control signal of each *** deal with the actuator saturation,an additional auxiliary dynamical system is *** is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately *** simulation examples are conducted to verify the presented adaptive fuzzy controller design.
This paper introduces GLOW-ENV, an intelligent Internet of Everything (IoE)-driven mobile application designed with the objective of integrating real-time glucose monitoring data and environmental metrics to enhance d...
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With the growth of big data in the past few decades, compression has become inseparable from data generation. The data generated daily across different platforms are correlated: friend networks on Facebook and Instagr...
With the growth of big data in the past few decades, compression has become inseparable from data generation. The data generated daily across different platforms are correlated: friend networks on Facebook and Instagram, contact networks in subsequent days, and many more. This raises the question of compressing a dataset using another correlated dataset. For instance, can we compress the Facebook graph of friends when we know Instagram’s graph? This can be cast as the classical problem of source coding with side information, and the answer is known to be positive when the graphs are "labeled" and/or aligned, meaning we need to know the node corresponding to Jon Doe in both Facebook and Instagram graphs. The classical idea is to utilize joint typicality to decide whether two graphs are correlated or not. In practice, graphs are often not aligned and/or the labels are concealed to keep the identity of the users private. In these scenarios, classical ideas are no longer applicable as joint typicality highly depends on the ordering of sequences. In this work, we prove for the first time the existence of lossless graph compression schemes that utilize unlabeled side information and improve the compression rate. In order to do that, we design binning along with a novel testing criterion that relies on graph matching, the closely related quadratic assignment problem and its asymptotic properties.
The Hamming distance, a fundamental measure of dissimilarity between data points, plays a crucial role in various fields, including error detection, machine learning, and genomic sequence alignment, where it is common...
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ISBN:
(数字)9783982633619
The Hamming distance, a fundamental measure of dissimilarity between data points, plays a crucial role in various fields, including error detection, machine learning, and genomic sequence alignment, where it is commonly used for identifying mismatches in nucleotide or protein sequences. This work introduces two implementations for computing Hamming distances for sequence alignment: synchronous and asynchronous matrix-based approaches. While most existing implementations rely on vector-based methods due to their simplicity and ease of use, they are not efficient for large-scale data. Our work focuses on enhancing performance by introducing matrix-based implementations that significantly improve computational efficiency and scalability. Our asynchronous implementation showcases Julia for sequential task flow and PaRSEC for parameterized task graph execution models on homogeneous and heterogeneous architectures. CPU computations use INT8 GEMM from oneMKL, while GPU implementations employ Tensor/Matrix Core INT8 GEMM from cuBLAS/hipBLAS and 1-bit TensorOps GEMM capabilities from CUTLASS. For constructing bitmask matrices on GPUs, we develop both a naive CUDA implementation using global memory and an optimized implementation utilizing shared memory at the warp level, with the optimized version achieving a 5X speedup over the naive approach. The results demonstrate significant performance improvements, with the asynchronous matrix-based implementation achieving up to 284X speedup over the vector-based approach on CPUs, while the asynchronous GPU-enabled implementation on A100 GPUs delivers a 15X speedup compared to the CPU matrix-based approach and a three orders of magnitude improvement over the CPU vector-based approach. Furthermore, the asynchronous implementation of PaRSEC scales well on up to 256 nodes of Summit and Frontier. These advancements highlight the scalability and efficiency of matrix-based Hamming distance computation, leveraging GPU acceleration and advan
The topology selection plays a key role in minimizing the losses and improving the output waveform quality of an inverter. In addition, increasing the switching frequency of an inverter help to reduce the size of EMI ...
The topology selection plays a key role in minimizing the losses and improving the output waveform quality of an inverter. In addition, increasing the switching frequency of an inverter help to reduce the size of EMI filters resulting in power density improvement. Use of wide-bandgap device (like SiC devices) enables high switching frequency operation in power electronic converters. However, due to low gate charge and small junction capacitance of SiC devices, the SiC-based inverter is more likely to be influenced by side-effects of fast switching transition like undesired ringing, larger voltage overshoot and mistriggerig due to miller-effect. Parasitic inductances of multiple power loops and gate loops within the inverter leg play a key role in these undesired effects, however, a proper design of PCB-layout can reduce these effects. In this paper, a comparison is conducted between a T-type and 2-level inverter topologies for motor drive applications. Furthermore, a placement configuration of components along with the PCB layout are proposed for a T-type leg to improve its switching transition behavior by reducing the power and gate loop parasitic inductances. The parasitic inductances of proposed configuration are estimated using FEA simulation, and the estimated values are used to simulate the switching transition behavior of a T-type leg. Finally, a Double Pulse Test (DPT) is executed to demonstrate the accurate switching transition behaviour of a T-type leg which is designed with the proposed PCB layout and component placement.
Nonclassical biphoton wavefunctions reside in a higher-dimensional Hilbert space than classical or single-photon wavefunctions. Using the separability that holds for both spatial and multi-photon dimensions, we genera...
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Nonclassical biphoton wavefunctions reside in a higher-dimensional Hilbert space than classical or single-photon wavefunctions. Using the separability that holds for both spatial and multi-photon dimensions, we genera...
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Cu(In,Ga)Se2-based solar cells typically use a CdS buffer layer, even though its relatively low bandgap causes parasitic absorption. While alternatives to CdS have been explored in other studies, limited results have ...
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This paper addresses the bearing-only formation tracking problem for heterogeneous nonlinear multi-robot systems. In contrast to position and distance-based formation algorithms, the robots can only measure the bearin...
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This paper addresses the bearing-only formation tracking problem for heterogeneous nonlinear multi-robot systems. In contrast to position and distance-based formation algorithms, the robots can only measure the bearing information from their neighbors to achieve cooperation while the state information is unavailable. This characteristic is able to be implemented in the hardware to reduce the requirements of the sensors. We construct a compensation function in the proposed controller to eliminate the effect of the unknown nonlinear terms in the system. This compensation function is also based on bearing measurements, which guarantees that the overall controller is bearing-only. The stability of the proposed formation tracking strategy can be ensured by Lyapunov techniques. Moreover, we analyze the performance of the protocol for moving leaders, where the formation tracking error can be restricted in a bounded set. Finally, the simulation results are presented to validate the feasibility of the proposed algorithm for both fixed and moving leaders.
The gradual decommissioning of fossil fuel-driven power plants, that traditionally provide most operational flexibility in power systems, has led to more frequent grid stability issues. To compensate for the lack of f...
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