Multi-Channel Fusion Classification Method Based on Time-Series Data

Article Engineering, Electrical & Electronic

Asymptotic Tracking Control for Nonaffine Systems With Disturbances

Shubo Wang

Summary: This article presents an adaptive asymptotic tracking control method with prescribed performance function for a class of nonaffine systems with unknown disturbances. By transforming the nonaffine system into an affine system, introducing a prescribed performance function, and utilizing the robust integral of the sign of the error (RISE) feedback term, the proposed control scheme achieves asymptotic tracking performance with guaranteed prescribed performance.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS (2022)

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Article Physics, Multidisciplinary

Distributed Deep Fusion Predictor for a Multi-Sensor System Based on Causality Entropy

Xue-Bo Jin et al.

Summary: This paper proposes a trend prediction method based on sensor data, which uses causality entropy and series causality coefficient to select high causal measurements as input data, and utilizes Bayesian method and multi-layer perceptron to build the prediction model. Experimental results demonstrate the proposed method can effectively enhance the prediction performance of multi-sensor systems.

ENTROPY (2021)

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Review Chemistry, Analytical

The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods

Xue-Bo Jin et al.

Summary: This paper reviews the development of traditional and modern state estimation methods, focusing on model-driven and data-driven approaches, as well as discussing the research results of hybrid filters. The main algorithms of each method are provided for beginners to have a clearer understanding, along with the future development trends in state estimation field being discussed.

SENSORS (2021)

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Article Agriculture, Multidisciplinary

Multi-stream hybrid architecture based on cross-level fusion strategy for fine-grained crop species recognition in precision agriculture

Jianlei Kong et al.

Summary: The MCF-Net model proposed in this paper combines the requirements for identifying different crop species from actual farmland scenes, and utilizes the cross-stage partial network (CSPNet) as the backbone module, three parallel sub-networks, and a cross-level fusion module. By leveraging massive fine-granulometric information, MCF-Net has superior representation ability for distinguishing interclass discrepancies and tolerating intra-class variances.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

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Article Energy & Fuels

Adaptive Predefined Performance Sliding Mode Control of Motor Driving Systems With Disturbances

Shubo Wang et al.

Summary: This paper presents a predefined time sliding mode control method for dual-inertia driving systems with unknown disturbances. An adaptive law is used to estimate unknown upper boundary parameters to eliminate the effects of unknown dynamics, achieving fast convergence rate of tracking error. The efficacy of the proposed approach is validated through comparative experiments.

IEEE TRANSACTIONS ON ENERGY CONVERSION (2021)

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Article Computer Science, Artificial Intelligence