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PDE-Based Deployment of Heterogeneous Nonlinear Multiagents: A Single-Point control Scheme

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第1期21卷 30-39页

作者： Man, Jingtao Xiao, Qiang Sheng, Yin Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

This article develops a methodology employing partial differential equations (PDEs) to facilitate the exponential deployment of large-scale heterogeneous nonlinear multiagent systems (MASs). The considered MASs comprise a multitude of nonlinear first-order agents (FOAs) and second-order agents (SOAs). Two heterogeneous nonlinear PDEs are established to model the considered MASs by designing appropriate network communication protocols. Unlike previous PDE-based approaches for multiagent deployment, the topological weights between neighboring agents are defined as series-dependent. An informed agent, which is able to measure the location information of other agents and transmit its location information to neighboring agents through the communication network, is placed between the final FOA and the initial SOA. This novel network-based control scheme is referred to as single-point control, which could ensure the well-posedness and exponential stability of the error system. Accordingly, pointwise and distributed measurements are employed for delay-free and time-delayed cases, respectively. Numerical examples are provided in 3-D space to substantiate the obtained theoretical results.

关键词： Mathematical models Logic Informatics Formation control Velocity measurement Space heating Protocols Propagation Position measurement Partial differential equations Heterogeneous nonlinear multiagent systems (MASs) partial differential equations (PDEs)-based methodology pointwise and distributed measurements series-dependent topological weights single-point control

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Cyclic transitions of DNA origami dimers driven by thermal cycling

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NANOTECHNOLOGY 2023年第6期34卷 065601-065601页

作者： Chen, Zhekun Chen, Kuiting Xie, Chun Liao, Kangchao Xu, Fei Pan, Linqiang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc & Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China

It is widely observed that life activities are regulated through conformational transitions of biological macromolecules, which inspires the construction of environmental responsive nanomachines in recent years. Here we present a thermal responsive DNA origami dimers system, whose conformations can be cyclically switched by thermal cycling. In our strategy, origami dimers are assembled at high temperatures and disassembled at low temperatures, which is different from the conventional strategy of breaking nanostructures using high temperatures. The advantage of this strategy is that the dimers system can be repeatedly operated without significant performance degradation, compared to traditional strategies such as conformational transitions via i-motif and G-quadruplexes, whose performance degrades with sample dilution due to repeated addition of trigger solutions. The cyclic conformational transitions of the dimers system are verified by fluorescence curves and AFM images. This research offered a new way to construct cyclic transformational nanodevices, such as reusable nanomedicine delivery systems or nanorobots with long service lifetimes.

关键词： DNA nanostructures DNA origami conformational transitions thermal cycling

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Current disturbance compensation of continuous model predictive control scheme for PMSMs

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ISA TRANSACTIONS 2024年 155卷 92-103页

作者： Luo, Pan Zhang, Sai Shen, Anwen Luo, Xin Tang, Qipeng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

During the operation of a permanent magnet synchronous motor, limitations imposed by digital chips inevitably result in certain delays. Additionally, external environmental factors introduce variations in motor parameters. This study aims to comprehensively analyze these issues. Firstly, the control delay and disturbances caused by motor parameter changes are transformed into current disturbances using a uniform approach. Secondly, various sliding mode model predictive controllers are designed to effectively suppress the current disturbances arising from aforementioned reasons. Moreover, considering controller implementation aspects, this paper thoroughly discusses the influence of core controller parameters on current disturbances and their adaptability toward different parameter mismatches. Furthermore, extensive examination is conducted on global stability conditions for controller realization. Finally, experimental results validate that the proposed methods successfully optimize current disturbances originating from aforementioned causes.

关键词： Model predictive control Current disturbance Parameter mismatch Permanent magnet synchronous motor

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Zero-Shot Defect Detection With Anomaly Attribute Awareness via Textual Domain Bridge

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IEEE SENSORS JOURNAL 2025年第7期25卷 11759-11771页

作者： Zhang, Zhe Chen, Shu Huang, Jian Ma, Jie Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China China Nucl Power Operat Technol Corp Ltd Wuhan 430074 Peoples R China

Visual defect detection is crucial for industrial quality control in intelligent manufacturing. Previous research requires target-specific data to train the model for each inspection task. However, due to the challenges of collecting proprietary data and model-training time costs, zero-shot defect detection (ZSDD) has become an emerging topic in the field. ZSDD, which requires models trained with auxiliary data, can detect defects on different products without target-data training. Recently, large pretrained vision-language models (VLMs), such as contrastive language-image pre-training model (CLIP), have demonstrated revolutionary generality with competitive zero-shot performance across various downstream tasks. However, VLMs have limitations in defect detection, which are designed to focus on identifying category semantics of the objects rather than sensing object attributes (defective/nondefective). The current VLMs-based ZSDD methods require manually crafted text prompts to guide the discovery of anomaly attributes. In this article, we propose a novel ZSDD method, namely attribute-aware CLIP, to adapt CLIP for anomaly attribute discovery without designing specific textual prompts. The core is designing a textual domain bridge, which transforms simple general textual prompt features into prompt embeddings better aligned with the attribute awareness. This enables the model to perceive the attributes of objects by text-image feature matching, bridging the gap between object semantic recognition and attribute discovery. Additionally, we perform component clustering on the images to break down the overall object semantics, encouraging the model to focus on attribute awareness. Extensive experiments on 16 real-world defect datasets demonstrate that our method achieves state-of-the-art (SOTA) ZSDD performance in diverse class-semantic datasets.

关键词： Defect detection Feature extraction Semantics Bridges image reconstruction Data models Visualization Training Sensors Manufacturing Attribute awareness component clustering defect detection intelligent manufacturing textual domain bridge vision-language model (VLM) zero-shot

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SDI: A sparse drift identification approach for force/torque sensor calibration in industrial robots

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NEUROCOMPUTING 2025年 620卷

作者： Qiao, Xuechun Xu, Chenxuan Wang, Yasen Ma, Guijun Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China China Telecom Res Inst Guangzhou 510630 Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China

Calibrating force/torque (F/T) sensor drift is an enduring objective for robotic precise force control. This article presents a novel drift identification method to discover the dynamics of F/T sensor drifts from noisy measurement data, which is conducive to accurate sensor drift compensation. In the drift identification method, a linear dynamical model with measurement noise is formulated to characterize the evolution of sensor drift, and an expectation-maximization optimization framework which integrates Kalman smoothing with sparse Bayesian learning is put forward to identify the parameters of the linear dynamical model using F/T sensor measurement data. The effectiveness of the proposed drift identification method is validated on extensive robotic experiments including scenarios with unloaded mass, loaded mass, and contact force. Experimental results demonstrate the superiority of the proposed drift identification method compared to the conventional least square method for sensor calibration.

关键词： Force/torque sensor Drift calibration Expectation-maximization optimization Kalman smoothing Sparse Bayesian learning Industrial robots

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A novel brain-inspired hierarchical perception-association circuit based on memristor arrays

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2023年 171卷

作者： Chen, Liangyu Wang, Xiaoping Chen, Zhanfei Yang, Chao Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist China Key Lab Image Proc & Intelligent Control Educ Wuhan 430074 Peoples R China Key Lab Brain Inspired Intelligent Syst Wuhan 430074 Peoples R China

In the brain, primary sensory cells can efficiently perceive multimodal stimuli, and then associative memory cells perform an advanced bidirectional associative memory function with perceived information. Here, a brain-inspired hierarchical perception-association circuit based on memristor arrays is proposed. Firstly, a memristive reservoir computing circuit is designed to simulate a low-level perceptual function, which mainly comprises dynamic analog reservoirs, memristor arrays, and analog integrators, enabling efficient spatio-temporal information processing. Secondly, a spiking bidirectional associative memory memristive circuit, as the core of the whole circuit, is proposed to mimic a high-level associative function, which mainly consists of memristor arrays, current amplifiers, and leaky integrate-and-fire neuron circuits, implementing multimodal associative learning. The simulation results in LTspice show that the modified neuron circuit exhibits 66x improvement in energy efficiency, and the proposed circuit can precisely perform the letter association and vision-audio association tasks in a spiking fashion with an average firing energy consumption of 230 pJ/spike, which has a great potential to be embedded in mobile robotic platforms.

关键词： Spiking bidirectional associative memory Memristor arrays Brain-inspired architecture Multimodal association Reservoir computing

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Prescribed performance control of a link-type exoskeleton powered by pneumatic muscles with virtual elasticity

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NONLINEAR DYNAMICS 2024年第12期112卷 10043-10060页

作者： Cao, Yu Zhang, Mengshi Huang, Jian Mohammed, Samer Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China Wuhan United Imaging Healthcare Surg Technol Co Lt Wuhan Hubei Peoples R China Univ Paris Est Creteil UPEC Lab Image Signal & Intelligent Syst LISSI F-94400 Vitry Sur Seine Pairs France

This paper presents a rehabilitation exoskeleton featuring a link-type design, driven by pneumatic muscles (PMs), with the driving torques transmitted to the leg orthoses via multiple linkages. The inherent complexity of this link-type exoskeleton presents significant challenges in both modeling and control. To address these challenges, we construct constrained kinematics and dynamics through geometric analysis, and introduce a robust prescribed performance controller with a virtual elastic element (PPC-VE) to enhance the safety of passive gait training. The controller has the capability to directly adjust the intensity of chattering in control inputs and ensure system transient/steady states performance by introducing a non-zero proxy mass and an error transformation. Theoretical analysis indicated the uniform ultimate boundedness of the states, with varying behaviors observed in the controller as the proxy mass changed. Simulation and experimental results demonstrated the validity of the dynamic model, and the proposed controller effectively enhanced system safety by addressing output constraints and reducing abrupt variations in control inputs.

关键词： Link-type exoskeleton Pneumatic muscle System modeling Prescribed performance control Virtual elasticity

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Passivity-Based controller Design of PCC Voltage Feedforward Active Damping for Grid-Connected Inverters

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2024年第8期71卷 8752-8762页

作者： Ye, Jie Wang, Haozhe Li, Baojin Huang, Yukai Xu, Jinbang Shen, Anwen Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Natl Key Lab Sci & Technol Multispectral Informat Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

The inherent resonance of LCL filter tends to result in the grid-connected inverter system oscillating due to the variation of the grid impedance at the point of common coupling (PCC), so damping needs to be implemented to ensure the asymptotic stability. This article develops a novel and sensorless PCC voltage feedforward active damping (PCCVF-AD) control strategy, which includes a generic controller and a resonant compensation term, and then models the input admittance of current-controlled inverter system. Thereafter, based on the frequency-domain passivity theory, the stability criterion of system is transformed to the real part of the inverter input admittance, thus proposing a well-established PCCVF-AD controller design scheme. The proposed PCCVF-AD is designed to ensure the passivity of inverter input admittance in all frequencies, thereby achieving the plug-and-play capability that the inverter can be connected to the grid regardless of the grid impedance. The presented analysis results are verified by experiments.

关键词： Damping Inverters Asymptotic stability Power system stability Impedance Stability criteria Voltage control Grid-connect inverter point of common coupling voltage feedforward active damping (PCCVF-AD) passivity theory stability

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Homogeneous domination-based composite adaptive control strategy for perturbed chain of integrators with mismatched disturbances

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NONLINEAR DYNAMICS 2024年第17期112卷 15399-15411页

作者： Xu, Xingchen Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Mini Wuhan 430074 Peoples R China

In this paper, a composite adaptive control law by utilizing the homogeneous domination-based and the disturbance observer-based method is designed to stabilize a class of perturbed nonlinear system. Inspired by the design of homogeneous domination-based approach and adaptive control algorithm with its identification of the uncertain parameters, a series of virtual controllers are elaborately designed in recursive procedures to counteract system nonlinearities and parameter perturbations. Meanwhile, the mismatched disturbances which exist in channels of states, are compensated in a recursive way via a disturbance estimation and compensation method with the recognized parameters. Both the design framework and stability analysis provide a comprehensive idea in practical implementations. Comparative numerical simulation results of a robot arm system verify performances of the proposed method with respect to several investigations.

关键词： Homogeneous domination approach Composite adaptive control Mismatched disturbances Robot arm system

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Tightly coupled stereo vision-inertial odometry based on point and line feature

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MEASUREMENT SCIENCE AND TECHNOLOGY 2025年第1期36卷

作者： Peng, Gang Cao, Yihao Chen, Shanliang Guo, Yubo He, Dingxin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Minist Educ China Engn Res Ctr Autonomous Intelligent Unmanned Syst Wuhan 430074 Peoples R China

To improve the accuracy and robustness of visual simultaneous localization and mapping (SLAM) in low-texture environments, this paper proposes a robust and fast stereo vision inertial SLAM pose estimation method that combines point and line features with an inertial measurement unit (IMU). The method tightly couples visual point and line features with IMU constraints, forming a least-squares problem through the error of each constraint term for nonlinear optimization. To address the issues of over-segmentation and time consumption in traditional line segment detection (LSD) algorithms, an improved LSD algorithm is adopted to accelerate line feature extraction. This approach merges nearby line segments based on spatial geometric relationships and filters out invalid segments, improving the time efficiency of the algorithm. Finally, experiments conducted in low-texture environments demonstrate that our algorithm achieves high localization accuracy and robustness.

关键词： line feature pose measurement tightly coupled real time visual-inertial odometry

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