Mengyao Wang - IEEE Xplore Author Profile

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Author details

Mengyao Wang

Publications

6

Citations

14

Publications by Year

20222025

Co-Authors:

Longlei BaiZhiqiang CaoHongmin GaoJiangbo GengLizeng Gong

Show All Co-Authors (26)

Mengyao Wang

Affiliation

State Key Laboratory of Multimodal Artificial Intelligence Systems

Institute of Automation

Chinese Academy of Sciences, Beijing, China

School of Artificial Intelligence

University of Chinese Academy of Sciences

Beijing, China

Publication Topics

Evaluation Index,
Optimization Algorithm,
Abundance Data,
Accurate Identification,
Actual Scene,
Adam Algorithm,
Adam Optimization Algorithm,
Additional Hardware,
Analytic Hierarchy Process,
Analytical Methods,
Atmospheric Water Vapor,
Attention Mechanism

Biography

Mengyao Wang received the B.Sc. degree in communications engineering from Jilin University, Changchun, China, in 2023. She is currently working toward the M.Sc. degree in electronic and information engineering with Harbin Engineering University, Harbin, China.,Her major research direction is undersea wireless power transfer and simultaneous wireless power and data transfer.(Based on document published on 12 December 2024).

Publications

6

Citations

14

Publications by Year

20222025

Co-Authors:

Longlei Bai
Zhiqiang Cao
Hongmin Gao
Jiangbo Geng
Lizeng Gong

Show All Co-Authors (26)

Author's Published Works

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Showing 1-25 of 264 results

Journals (139)

Conferences (119)

Early Access Articles (4)

Magazines (2)

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Peter X. Liu(124)
Peter Xiaoping Liu(75)
P.X. Liu(48)
Chunquan Li(27)
Huanqing Wang(27)
Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada(76)
Department of Systems and Computer Engineering, Carleton University, Ottawa, ONT, Canada(67)
Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada(64)
School of Information Engineering, Nanchang University, Nanchang, China(40)
School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China(33)
IEEE Transactions on Instrumentation and Measurement(31)
IEEE Access(16)
IEEE Transactions on Cybernetics(14)
IEEE/ASME Transactions on Mechatronics(11)
IEEE Transactions on Industrial Electronics(9)
IEEE(263)
KICS(1)
Media(10)
Datasets(1)
Banff, AB, Canada(7)
Niagara Falls, ON, Canada(6)
Victoria, BC, Canada(6)
Shanghai, China(5)
Kobe, Japan(4)
Nonlinear Systems(47)
Adaptive Control(43)
Time Delay(40)
Tracking Error(36)
Force Feedback(35)

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Results

PV-PASBLS: A Multimodal Point-View Fusion Model Based on Parameter Adaptive Stacked Broad Learning System for 3D Shape Recognition

Zhiyuan Liao;Chunquan Li;Hui Jin;Beike Li;Zhijun Zhang;Junzhi Yu;Peter X. Liu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Early Access Article |

Most existing multimodal point-view fusion models for 3D shape recognition typically improve recognition accuracy through complex feature fusion mechanisms. However, these mechanisms significantly increase the model’s complexity and computational cost. To address this issue, a novel multimodal point-view fusion model based on a parameter adaptive stacked broad learning system (PV-PASBLS) for 3D sh...Show More

PV-PASBLS: A Multimodal Point-View Fusion Model Based on Parameter Adaptive Stacked Broad Learning System for 3D Shape Recognition

Zhiyuan Liao;Chunquan Li;Hui Jin;Beike Li;Zhijun Zhang;Junzhi Yu;Peter X. Liu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Early Access Article |

Design and Control of a Fully Actuated Aerial Manipulator System for Measuring the Thickness of Metal Facilities

Shuang Hao;Juzheng Mao;Junyi Zhang;Xiangyang Zhao;Guangming Song;Aiguo Song;Peter Xiaoping Liu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

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An aerial manipulator (AM) system for thickness measurement of metal facilities is introduced in this article, which includes a fully actuated flying platform and an end effector. The AM utilizes the fully actuated advantage of the flying platform to apply controlled contact forces to the environment without the need for complex robotic manipulators. An end effector is designed, which includes an ...Show More

Design and Control of a Fully Actuated Aerial Manipulator System for Measuring the Thickness of Metal Facilities

Shuang Hao;Juzheng Mao;Junyi Zhang;Xiangyang Zhao;Guangming Song;Aiguo Song;Peter Xiaoping Liu

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

An Arbitrarily Predefined-Time Convergent RNN for Dynamic LMVE With Its Applications in UR3 Robotic Arm Control and Multiagent Systems

Boyu Zheng;Chunquan Li;Zhijun Zhang;Junzhi Yu;P. X. Liu

IEEE Transactions on Cybernetics

Year: 2025 | Volume: 55, Issue: 4 | Journal Article |

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Zeroing neural network (ZNN), as a special type of recurrent neural network (RNN), is very competitive in solving time-varying linear matrix-vector equations. Recently, various ZNNs with predefined-time convergence (PTC) capabilities have been reported. Such ZNNs with PTC capabilities can achieve the predefined convergence time via explicitly presetting multiple parameters related to the upper bou...Show More

An Arbitrarily Predefined-Time Convergent RNN for Dynamic LMVE With Its Applications in UR3 Robotic Arm Control and Multiagent Systems

Boyu Zheng;Chunquan Li;Zhijun Zhang;Junzhi Yu;P. X. Liu

IEEE Transactions on Cybernetics

Year: 2025 | Volume: 55, Issue: 4 | Journal Article |

Novel CNN-Based Approach for Burn Severity Assessment and Fine-Grained Boundary Segmentation in Burn Images

Mahla Abdolahnejad;Justin Lee;Hannah Chan;Alex Morzycki;Olivier Ethier;Anthea Mo;Peter X. Liu;Joshua N. Wong;Colin Hong;Rakesh Joshi

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

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Burn injuries, resulting from thermal, chemical, and electrical mechanisms, require prompt and accurate assessment for effective treatment. The primary method, relying on visual and tactile evaluations, offers 50%–80% accuracy, while noninvasive methods such as laser Doppler imaging (LDI) reach up to 97% accuracy. This article presents a machine learning (ML) pipeline for assessing burn severity a...Show More

Novel CNN-Based Approach for Burn Severity Assessment and Fine-Grained Boundary Segmentation in Burn Images

Mahla Abdolahnejad;Justin Lee;Hannah Chan;Alex Morzycki;Olivier Ethier;Anthea Mo;Peter X. Liu;Joshua N. Wong;Colin Hong;Rakesh Joshi

IEEE Transactions on Instrumentation and Measurement

Year: 2025 | Volume: 74 | Journal Article |

SSVEPPoolformer: An Improved Poolformer Model With the Adaptive Denoising Algorithm for SSVEP-EEG Signal Classification

Chunquan Li;Zhiyuan Liao;Yuxin Cheng;Zitao Wang;Junyun Wu;Ruijun Liu;Peter X. Liu

IEEE Transactions on Consumer Electronics

Year: 2025 | Early Access Article |

Most EEG classification algorithms based on steady-state visual evoked potentials (SSVEP-EEG) require filtering for denoising. However, manually set thresholds may inadvertently remove useful information, leading to a loss of significant signal features. Additionally, most deep learning-based SSVEP-EEG classification models have limited global feature extraction capabilities, and the self-attentio...Show More

SSVEPPoolformer: An Improved Poolformer Model With the Adaptive Denoising Algorithm for SSVEP-EEG Signal Classification

Chunquan Li;Zhiyuan Liao;Yuxin Cheng;Zitao Wang;Junyun Wu;Ruijun Liu;Peter X. Liu

IEEE Transactions on Consumer Electronics

Year: 2025 | Early Access Article |

Observer-Based Adaptive Fixed-Time Sensor Fault Compensation Control for Uncertain Nonlinear Systems

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Cybernetics

Year: 2025 | Volume: 55, Issue: 3 | Journal Article |

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This article focuses on an observer-based adaptive sensor fault compensation fixed-time tracking control problem for uncertain nonlinear systems. A sixth-power Lyapunov function is designed for the first time which lays the foundation to construct the effective adaptive fixed-time fault compensation mechanism. Meanwhile, in the controller design procedure, owing to the existence of the sensor faul...Show More

Observer-Based Adaptive Fixed-Time Sensor Fault Compensation Control for Uncertain Nonlinear Systems

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Cybernetics

Year: 2025 | Volume: 55, Issue: 3 | Journal Article |

Facilitating Autonomous Driving Tasks With Large Language Models

Mengyao Wu;F. Richard Yu;Peter Xiaoping Liu;Ying He

IEEE Intelligent Systems

Year: 2025 | Volume: 40, Issue: 1 | Magazine Article |

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We explore how large language models (LLMs) can expedite and automate the learning process for autonomous driving tasks. This involves harnessing LLM knowledge to shape a learning framework and utilizing LLMs to guide the learning process. We conduct a case study to demonstrate LLMs’ ability to export driving rules. LLM outputs may not be entirely reliable for the direct handling of driving decisi...Show More

Facilitating Autonomous Driving Tasks With Large Language Models

Mengyao Wu;F. Richard Yu;Peter Xiaoping Liu;Ying He

IEEE Intelligent Systems

Year: 2025 | Volume: 40, Issue: 1 | Magazine Article |

Point Cloud Registration in Laparoscopic Liver Surgery Using Keypoint Correspondence Registration Network

Yirui Zhang;Yanni Zou;Peter X. Liu

IEEE Transactions on Medical Imaging

Year: 2025 | Volume: 44, Issue: 2 | Journal Article |

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Laparoscopic liver surgery is a newly developed minimally invasive technique and represents an inevitable trend in the future development of surgical methods. By using augmented reality (AR) technology to overlay preoperative CT models with intraoperative laparoscopic videos, surgeons can accurately locate blood vessels and tumors, significantly enhancing the safety and precision of surgeries. Poi...Show More

Point Cloud Registration in Laparoscopic Liver Surgery Using Keypoint Correspondence Registration Network

Yirui Zhang;Yanni Zou;Peter X. Liu

IEEE Transactions on Medical Imaging

Year: 2025 | Volume: 44, Issue: 2 | Journal Article |

A Point Cloud Registration Method Based on Segmenting Sphere Region Feature Descriptor and Overlapping Region Matching Strategy

Yirui Zhang;Jiabo Xu;Yanni Zou;Peter X. Liu

IEEE Sensors Journal

Year: 2024 | Volume: 24, Issue: 22 | Journal Article |

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Accurately registering point clouds is challenging due to three primary reasons: 1) it is difficult for point cloud feature descriptors to handle noise in complex scenes; 2) poorly descriptive features lead to incorrect sets of corresponding points; and 3) non-overlapping regions in the scene can adversely affect registration results. To address these issues, our approach consists of three key con...Show More

A Point Cloud Registration Method Based on Segmenting Sphere Region Feature Descriptor and Overlapping Region Matching Strategy

Yirui Zhang;Jiabo Xu;Yanni Zou;Peter X. Liu

IEEE Sensors Journal

Year: 2024 | Volume: 24, Issue: 22 | Journal Article |

Finite-Frequency Fault Estimation and Adaptive Event-Triggered Fault-Tolerant Consensus for LPV Multiagent Systems

Shanglin Li;Yangzhou Chen;Peter Xiaoping Liu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2024 | Volume: 54, Issue: 12 | Journal Article |

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This article investigates the problem of finite-frequency fault estimation (FE) and adaptive event-triggered fault-tolerant consensus for linear parameter-varying multiagent systems. A polytopic parameter-varying framework is introduced to represent the dynamics of each agent with internal model perturbation and parameter uncertainties. In order to reduce the conservatism brought by full-frequency...Show More

Finite-Frequency Fault Estimation and Adaptive Event-Triggered Fault-Tolerant Consensus for LPV Multiagent Systems

Shanglin Li;Yangzhou Chen;Peter Xiaoping Liu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2024 | Volume: 54, Issue: 12 | Journal Article |

Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna Systems

Zhan Liu;Zhiyuan Liao;Chunquan Li;Zhijun Zhang;Junzhi Yu;P. X. Liu

IEEE Transactions on Green Communications and Networking

Year: 2024 | Early Access Article |

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAS), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. Specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (QoS) requ...Show More

Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna Systems

Zhan Liu;Zhiyuan Liao;Chunquan Li;Zhijun Zhang;Junzhi Yu;P. X. Liu

IEEE Transactions on Green Communications and Networking

Year: 2024 | Early Access Article |

Stabilization of Impulsive Systems With Beyond-Interval Impulse Delays

Kun Wang;Peter Xiaoping Liu;Zheqi Yu

IEEE Transactions on Circuits and Systems I: Regular Papers

Year: 2024 | Volume: 71, Issue: 10 | Journal Article |

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This paper addresses the stabilization problem of linear impulsive systems with beyond-interval delays, for which state correlation exists between the current interval’s impulse state estimation and the historical feedback, making it difficult to obtain stability conditions for the system. In order to solve this problem, we develop a novel impulsive control method called interval partitioning, for...Show More

Stabilization of Impulsive Systems With Beyond-Interval Impulse Delays

Kun Wang;Peter Xiaoping Liu;Zheqi Yu

IEEE Transactions on Circuits and Systems I: Regular Papers

Year: 2024 | Volume: 71, Issue: 10 | Journal Article |

A Novel Variable-Parameter Variable-Activation-Function Finite-Time Neural Network for Solving Joint-Angle Drift Issues of Redundant-Robot Manipulators

Jinhua Deng;Chunquan Li;Rongling Chen;Boyu Zheng;Zhijun Zhang;Junzhi Yu;Peter Xiaoping Liu

IEEE/ASME Transactions on Mechatronics

Year: 2024 | Early Access Article |

This article presents a novel variable-parameter variable-activation-function finite-time neural network (VPA-FTNN) to deal with joint-angle drift issues of redundant-robotic arms. Different from most existing recurrent neural networks, VPA-FTNN establishes an error-based finite-time-convergence neural dynamics equation with variable-parameter and variable-activation-functions features so that it ...Show More

A Novel Variable-Parameter Variable-Activation-Function Finite-Time Neural Network for Solving Joint-Angle Drift Issues of Redundant-Robot Manipulators

Jinhua Deng;Chunquan Li;Rongling Chen;Boyu Zheng;Zhijun Zhang;Junzhi Yu;Peter Xiaoping Liu

IEEE/ASME Transactions on Mechatronics

Year: 2024 | Early Access Article |

Sequence Generation Completion Method and Resolution Scaling Network for Point Cloud Completion

Jiabo Xu;Yirui Zhang;Yanni Zou;Peter X. Liu

IEEE Transactions on Geoscience and Remote Sensing

Year: 2024 | Volume: 62 | Journal Article |

Cited by: Papers (1)

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Point cloud completion aims to predict the missing part for an incomplete 3-D shape. Existing point cloud completion methods based on deep learning complete the point cloud by extracting global features from the incomplete point cloud. However, such methods cannot generate a uniformly distributed point cloud and the accurate structure details of the object. To solve the problem, a novel method for...Show More

Sequence Generation Completion Method and Resolution Scaling Network for Point Cloud Completion

Jiabo Xu;Yirui Zhang;Yanni Zou;Peter X. Liu

IEEE Transactions on Geoscience and Remote Sensing

Year: 2024 | Volume: 62 | Journal Article |

A Collective and Continuous Rule Learning Framework Towards Enhanced Driving Safety and Decision Transparency

Mengyao Wu;F. Richard Yu;Peter Xiaoping Liu

IEEE Transactions on Vehicular Technology

Year: 2024 | Volume: 73, Issue: 10 | Journal Article |

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Deep reinforcement learning (DRL)-based driving policies enable connected and autonomous vehicles (CAVs) to adapt to complex environments but lack guarantees of safety and decision transparency. For this reason, we propose a hybrid decision-making system that integrates DRL with a learnable, rule-based safety module, wherein the latter offers enhanced driving safety and decision transparency. Howe...Show More

A Collective and Continuous Rule Learning Framework Towards Enhanced Driving Safety and Decision Transparency

Mengyao Wu;F. Richard Yu;Peter Xiaoping Liu

IEEE Transactions on Vehicular Technology

Year: 2024 | Volume: 73, Issue: 10 | Journal Article |

A Two-Pipeline Instance Segmentation Network via Boundary Enhancement for Scene Understanding

Chaofan Du;Peter Xiaoping Liu;Xiansong Song;Minhua Zheng;Changwei Wang

IEEE Transactions on Instrumentation and Measurement

Year: 2024 | Volume: 73 | Journal Article |

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For applications such as autonomous vehicles, instance segmentation of captured images about surrounding environments is critical, and in the meantime, these types of tasks require high accuracy as well. However, most existing models do not consider the extra computation caused by complex architectures and the poor ability of overly lightweight structures to capture semantic information. To enable...Show More

A Two-Pipeline Instance Segmentation Network via Boundary Enhancement for Scene Understanding

Chaofan Du;Peter Xiaoping Liu;Xiansong Song;Minhua Zheng;Changwei Wang

IEEE Transactions on Instrumentation and Measurement

Year: 2024 | Volume: 73 | Journal Article |

A Novel Head-Mounted Navigation Device Based on Vibrotactile Stimulation

Shimeng Ma;Peter Xiaoping Liu;Jinfeng Gao

IEEE Transactions on Instrumentation and Measurement

Year: 2024 | Volume: 73 | Journal Article |

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Despite the availability of guide dogs and sticks, visually impaired people still have difficulties in traveling and sometimes may encounter dangers. This article presents a novel head-mounted haptic navigation device, for which vibrotactile stimulation is employed at different locations of the head helmet. A set of different navigation instructions is provided through coding the sequential stimul...Show More

A Novel Head-Mounted Navigation Device Based on Vibrotactile Stimulation

Shimeng Ma;Peter Xiaoping Liu;Jinfeng Gao

IEEE Transactions on Instrumentation and Measurement

Year: 2024 | Volume: 73 | Journal Article |

Electricity Retail Plan Recommendation Method Based on Multigranular Hesitant Fuzzy Sets and an Improved Non-Negative Latent Factor Model

Yuanqian Ma;Ruinan Zheng;Yuhao Lu;Zhi Zhang;Yunchu Wang;Zhenzhi Lin;Li Yang;Hongle Liang;Peter Xiaoping Liu

IEEE Transactions on Energy Markets, Policy and Regulation

Year: 2024 | Volume: 2, Issue: 2 | Journal Article |

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Electricity retail companies can derive significant benefits from precise recommendations of electricity retail plans (ERPs). However, existing recommendation methods often assume that customers are proficient in evaluating all the attributes of ERPs, and overlook the fact that the accuracy of predicting missing information is closely tied to the objective function of customers’ satisfaction, whic...Show More

Electricity Retail Plan Recommendation Method Based on Multigranular Hesitant Fuzzy Sets and an Improved Non-Negative Latent Factor Model

Yuanqian Ma;Ruinan Zheng;Yuhao Lu;Zhi Zhang;Yunchu Wang;Zhenzhi Lin;Li Yang;Hongle Liang;Peter Xiaoping Liu

IEEE Transactions on Energy Markets, Policy and Regulation

Year: 2024 | Volume: 2, Issue: 2 | Journal Article |

An Improved Level Set Method for Reachability Problems in Differential Games

Wei Liao;Taotao Liang;Pengwen Xiong;Chen Wang;Aiguo Song;Peter X. Liu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2024 | Volume: 54, Issue: 5 | Journal Article |

Cited by: Papers (1)

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This study focuses on reachability problems in differential games. An improved level set (LS) method for computing reachable tubes (RTs) is proposed in this article. The RT is described as a sub-LS of a value function, which is the viscosity solution of a Hamilton–Jacobi (HJ) equation with running cost. We generalize the concept of RTs and propose a new class of RTs, which are referred to as cost-...Show More

An Improved Level Set Method for Reachability Problems in Differential Games

Wei Liao;Taotao Liang;Pengwen Xiong;Chen Wang;Aiguo Song;Peter X. Liu

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Year: 2024 | Volume: 54, Issue: 5 | Journal Article |

Adaptive Fixed-Time Control for High-Order Stochastic Nonlinear Time-Delay Systems: An Improved Lyapunov–Krasovskii Function

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Cybernetics

Year: 2024 | Volume: 54, Issue: 2 | Journal Article |

Cited by: Papers (20)

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In this article, the adaptive tracking control problem is considered for high-order stochastic nonlinear time-delay systems in fixed-time. Being different from existing results, an improved Lyapunov–Krasovskii function is designed, which can not only compensate for the time-delay term but also remove the obstacle from the high-order term. Due to the introduction of the Lyapunov–Krasovskii function...Show More

Adaptive Fixed-Time Control for High-Order Stochastic Nonlinear Time-Delay Systems: An Improved Lyapunov–Krasovskii Function

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Cybernetics

Year: 2024 | Volume: 54, Issue: 2 | Journal Article |

Compounding and Synchronization of Fractional Order Chaotic Systems With Prescribed Performance for Secure Communication

Zheqi Yu;Song Ling;Peter Xiaoping Liu;Huanqing Wang

IEEE Transactions on Circuits and Systems I: Regular Papers

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

Cited by: Papers (3)

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Fractional-order chaotic systems show great potential in secure communications because of their unique properties. In order to improve their encryption and anti-attack capabilities, a new compounding mechanism is developed for fractional-order multidrive and response chaotic systems. Rather than using simple addition, which is often employed in existing work, the compounding is based on multiplica...Show More

Compounding and Synchronization of Fractional Order Chaotic Systems With Prescribed Performance for Secure Communication

Zheqi Yu;Song Ling;Peter Xiaoping Liu;Huanqing Wang

IEEE Transactions on Circuits and Systems I: Regular Papers

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

Enhancing Robotic Tactile Exploration With Multireceptive Graph Convolutional Networks

Junjie Liao;Pengwen Xiong;Peter X. Liu;Zhijun Li;Aiguo Song

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 8 | Journal Article |

Cited by: Papers (4)

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While robotic tactile sensors have been developed to help robots to perceive and interact effectively with their surrounding environment by mimicking the structure and function of human skin, most of them overlook the role of near-contact behavior and data structure modeling in robotic perception, which limits robotic exploration capabilities. To address this problem, this article presents a novel...Show More

Enhancing Robotic Tactile Exploration With Multireceptive Graph Convolutional Networks

Junjie Liao;Pengwen Xiong;Peter X. Liu;Zhijun Li;Aiguo Song

IEEE Transactions on Industrial Electronics

Year: 2024 | Volume: 71, Issue: 8 | Journal Article |

Singularity-Free Adaptive Fixed-Time Tracking Control for MIMO Nonlinear Systems With Dynamic Uncertainties

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

Cited by: Papers (25)

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This brief focuses on adaptive neural fixed-time tracking control problem for the multi-input and multi-output (MIMO) nonlinear systems with dynamic uncertainty. In the controller design process, the difficulties are to overcome the multiple singularity problems. The hyperbolic tangent function and the piecewise function are invoked to deal with the singularity problems that occur in the process o...Show More

Singularity-Free Adaptive Fixed-Time Tracking Control for MIMO Nonlinear Systems With Dynamic Uncertainties

Ke Xu;Huanqing Wang;Peter Xiaoping Liu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2024 | Volume: 71, Issue: 3 | Journal Article |

An Interpretable Nonlinear Decoupling and Calibration Approach to Wheel Force Transducers

Lihang Feng;Sui Wang;Jiantao Shi;Pengwen Xiong;Chuang Chen;Di Xiao;Aiguo Song;Peter Xiaoping Liu

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 1 | Journal Article |

Cited by: Papers (3)

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The multi-dimensional force/torque decoupling and calibration is extremely crucial to increase the accuracy of the Wheel Force Transducer/Sensor (WFT). A novel interpretable nonlinear decoupling and calibration approach to WFT is presented. A physical interpretable prime-error framework is developed such that the linear prime part accounts for most force-voltage responses while the nonlinear error...Show More

An Interpretable Nonlinear Decoupling and Calibration Approach to Wheel Force Transducers

Lihang Feng;Sui Wang;Jiantao Shi;Pengwen Xiong;Chuang Chen;Di Xiao;Aiguo Song;Peter Xiaoping Liu

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 1 | Journal Article |

Improved Memory Event-Triggered Load Frequency Control in Multi-Area Power System With Renewable Energy

Xinxin Lv;Feng Qiao;Yonghui Sun;Venkata Dinavahi;Peter Xiaoping Liu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2024 | Volume: 71, Issue: 1 | Journal Article |

Cited by: Papers (6)

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To mitigate the data transmission burden, an new memory event-trigger scheme is developed for the load frequency control (LFC) of multi-area networked power systems with the integration of various new energy sources. $H_{\infty }$ stability criteria under less conservative conditions are established by utilizing an improved Lyapunov stability theory and a second-order Bessel-Legendre (B-L) inequ...Show More

Improved Memory Event-Triggered Load Frequency Control in Multi-Area Power System With Renewable Energy

Xinxin Lv;Feng Qiao;Yonghui Sun;Venkata Dinavahi;Peter Xiaoping Liu

IEEE Transactions on Circuits and Systems II: Express Briefs

Year: 2024 | Volume: 71, Issue: 1 | Journal Article |

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