4.6 Article

Global fixed-time stabilization for a class of switched nonlinear systems with general powers and its application

Journal

NONLINEAR ANALYSIS-HYBRID SYSTEMS
Volume 31, Issue -, Pages 56-68

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.nahs.2018.08.005

Keywords

Switched nonlinear systems; Common Lyapunov function; Adding a power integrator; Fixed-time stabilization

Funding

  1. National Nature Science Foundation of China [61873120, 61673243, 61703232, 61473265, 51675259]
  2. Project of Taishan Scholar of Shandong Province of China [TS20120529]
  3. PhD Programs Foundation of Ministry of Education of China [20123705110002]
  4. National Nature Science Foundation of Shandong Province [ZR2017QF013]
  5. High-level Talent Initial Funding of Nanjing Institute of Technology

Ask authors/readers for more resources

This paper investigates the problem of global fixed-time stabilization for a class of uncertain switched nonlinear systems with the general powers, namely, the powers of the considered systems can be different odd rational numbers, even rational numbers or both odd and even rational numbers. By skillfully using the common Lyapunov function method and the adding a power integrator technique, a common state feedback control strategy is developed. It is proved that the proposed controller can guarantee that the state of the resulting closed-loop system converges to zero for any given fixed time under arbitrary switchings. Simulation results of the liquid-level system are provided to show the effectiveness of the proposed method. (C) 2018 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Automation & Control Systems

Active disturbance rejection control design for high-order integral systems

Zhenlong Wu, Gengjin Shi, Donghai Li, Yanhong Liu, YangQuan Chen

Summary: This paper studies the design of active disturbance rejection control (ADRC) for high-order integral systems and proves the necessary condition for ADRC. The advantages of ADRC over proportional-integral-derivative (PID) controller are theoretically analyzed. A practical design procedure for ADRC is summarized using the single variable method, and comparative simulations and experiments are conducted to verify its performance.

ISA TRANSACTIONS (2022)

Article Engineering, Electrical & Electronic

Vision-Based Power Line Segmentation With an Attention Fusion Network

Lei Yang, Junfeng Fan, Shuai Xu, En Li, Yanhong Liu

Summary: Automatic power transmission line detection is crucial for smart grids, but it faces challenges due to complex backgrounds and lighting conditions. Recent advancements in deep learning have led to fast development in pixel-level object segmentation, but still lack in processing local contextual features and information loss. In this paper, a novel vision-based power line detection network with an encoder-decoder architecture is proposed. Attention and attention fusion blocks are introduced to address class imbalance and improve segmentation precision by capturing global contexts and fusing multi-scale features. Experimental results demonstrate the proposed network's good segmentation performance in real power line environments.

IEEE SENSORS JOURNAL (2022)

Article Automation & Control Systems

Observer-based Adaptive Robust Control of Soft Pneumatic Network Actuators

Guizhou Cao, Yanhong Liu, Zhiwei Zhu

Summary: This study proposes new observer-based adaptive robust controllers for PNAs, which address system uncertainties and unavailable states. The controllers utilize sliding patch-based observer and disturbance observer to achieve control. The stability of closed-looped systems is analyzed by the Lyapunov method, and the effectiveness of the controllers is verified through simulations and experiments.

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2022)

Article Automation & Control Systems

Stability analysis for nonlinear switched singular systems via T-S fuzzy modeling

Yanhong Liu, Huimin Zhi, Jumei Wei, Xunlin Zhu, Mingliang Xu, Rui Ma, Haiping Du

Summary: This paper investigates the stability of discrete nonlinear switched singular systems with unstable subsystems. New stability results for nonlinear switched singular systems are established by constructing an appropriate multiple discontinuous Lyapunov function and utilizing the characteristics of mode-dependent average dwell time switching signals. The T-S fuzzy modeling method is adopted to approximate the nonlinear switched singular systems and obtain general stability conditions in the form of linear matrix inequalities. Compared to the current results, our technique is more flexible and provides tighter dwell time boundaries. A numerical example is also provided to demonstrate the effectiveness of the proposed method.

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS (2022)

Article Computer Science, Artificial Intelligence

A shape-guided deep residual network for automated CT lung segmentation

Lei Yang, Yuge Gu, Benyan Huo, Yanhong Liu, Guibin Bian

Summary: This paper proposes a novel approach for automatic CT lung segmentation using an encoder-decoder framework and a shape-guided deep residual network. It effectively overcomes the complexity of CT scans and improves the accuracy of lung segmentation through multiscale feature extraction and boundary computation.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

A nondestructive automatic defect detection method with pixelwise segmentation

Lei Yang, Junfeng Fan, Benyan Huo, En Li, Yanhong Liu

Summary: Defect detection is crucial for product quality control and repair decision-making. Nondestructive testing (NDT) is effective, but faces challenges such as complex backgrounds and class imbalance. Deep learning has improved automatic defect detection, but limitations remain due to insufficient processing of local contextual features. A novel nondestructive defect detection network, NDD-Net, incorporating an attention fusion block (AFB) and a residual dense connection convolution block (RDCCB), outperforms other related models in segmenting microdefects.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Computer Science, Information Systems

Force Tracking Control of Functional Electrical Stimulation via Hybrid Active Disturbance Rejection Control

Benyan Huo, Ruishun Wang, Yunhui Qin, Zhenlong Wu, Guibin Bian, Yanhong Liu

Summary: This paper proposes a force tracking control method for upper limb based on functional electrical stimulation (FES). It modifies a Hammerstein model to describe the nonlinear dynamics of biceps brachii and presents a quick model identification method. To deal with the variation of muscle dynamics, a hybrid active disturbance rejection control (ADRC) is used. Simulation and experiments verify the performance of the proposed methods, which can suppress model uncertainty and improve tracking precision.

ELECTRONICS (2022)

Article Computer Science, Artificial Intelligence

PLE-Net: Automatic power line extraction method using deep learning from aerial images

Lei Yang, Junfeng Fan, Benyan Huo, En Li, Yanhong Liu

Summary: This paper proposes an end-to-end attention-based segmentation method for automatically extracting power lines from aerial images, which addresses the challenges of power line extraction by leveraging the contextual feature generation ability of deep learning. It introduces a self-attention block and a multi-scale feature enhance block to emphasize the power line regions and capture rich contextual relationships.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Automation & Control Systems

Multiperiodic Repetitive Control for Functional Electrical Stimulation-Based Wrist Tremor Suppression

Zan Zhang, Bing Chu, Yanhong Liu, Haichuan Ren, Zhe Li, David H. Owens

Summary: The study proposed a new FES-based multiperiodic repetitive control scheme for suppressing multiple frequency wrist tremors, and experimental results showed significant effectiveness.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2022)

Article Computer Science, Artificial Intelligence

A light defect detection algorithm of power insulators from aerial images for power inspection

Lei Yang, Junfeng Fan, Shouan Song, Yanhong Liu

Summary: In this study, a novel defect identification algorithm based on deep learning and transfer learning models is proposed for power insulators with missing-cap defects. The algorithm combines SPP and MobileNet networks to propose a fast and accurate lightweight DCNN model for insulator location and removing complex background interference. Additionally, an improved transfer learning model based on feature fusion is introduced for high-precision defect identification of power insulators using DS evidence theory.

NEURAL COMPUTING & APPLICATIONS (2022)

Article Energy & Fuels

Load frequency regulation for multi-area power systems with renewable sources via active disturbance rejection control

Zhenlong Wu, Yanhong Liu, YangQuan Chen, Donghai Li, Bingnan Li, Feng Zhu

Summary: This paper focuses on load frequency regulation for multi-area power systems with renewable sources using a cascaded ADRC approach. Simulations demonstrate that the proposed cascaded ADRC has strong power suppression capabilities and can quickly return to stability during load variations.

ENERGY REPORTS (2022)

Article Computer Science, Information Systems

Grouping-Based Optimization Method for Multirobot System Pattern Formation

Tingting Wang, Fangfang Zhang, Jianbin Xin, Yanhong Liu

Summary: This article presents a novel optimization method for multirobot formation in an obstacle environment. By utilizing a specific grouping strategy and coordination within and between groups, the proposed method achieves efficient formation of optimal patterns.

IEEE SYSTEMS JOURNAL (2022)

Article Engineering, Multidisciplinary

A multi-scale global attention network for blood vessel segmentation from fundus images

Ge Gao, Jianyong Li, Lei Yang, Yanhong Liu

Summary: Accurate segmentation of retinal fundus vessel images is crucial for clinical diagnosis. This paper proposes a new multi-scale global attention network (MGA-Net) for automatic segmentation using deep learning, and demonstrates its effectiveness on multiple datasets.

MEASUREMENT (2023)

Article Engineering, Electrical & Electronic

An Automatic Deep Segmentation Network for Pixel-Level Welding Defect Detection

Lei Yang, Shouan Song, Junfeng Fan, Benyan Huo, En Li, Yanhong Liu

Summary: Accurate welding defect location is crucial for modern manufacturing. A novel welding defect location method is proposed with an attention-guided segmentation network, which utilizes multiscale feature fusion and attention blocks to enhance defect localization and segmentation, effectively addressing issues of class imbalance and microdefects.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)

Article Automation & Control Systems

Multimuscle Functional-Electrical-Stimulation-Based Wrist Tremor Suppression Using Repetitive Control

Zan Zhang, Bing Chu, Yanhong Liu, Zhe Li, David H. Owens

Summary: This article proposes a multi-muscle FES-based wrist tremor suppression method that considers the characteristics of wrist motion. By combining a feedback controller and a feedforward linearization controller, the method improves tremor suppression performance and reduces muscle fatigue by regulating FES levels effectively. Experimental results show significant improvements over existing single-muscle FES methods.

IEEE-ASME TRANSACTIONS ON MECHATRONICS (2022)

Article Automation & Control Systems

Aperiodic dynamic event-triggered control for linear systems: A looped-functional approach

Yihao Xu, Alexandre Seuret, Kun Liu, Senchun Chai

Summary: The recent literature on event-triggered control has shown the potential of dynamic periodic event-triggered control. The benefit of considering periodic event-triggered control is to avoid the Zeno phenomenon. This paper proposes a generic framework to emulate aperiodic dynamic event-triggered control law and relaxes the constraint on the periodicity of the allowable sampling instants.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Non-smooth competitive systems and complex dynamics induced by linearly dependent feedback control

Yuan Tian, Chunxue Li, Jing Liu

Summary: Competition is a common biological relationship in nature, especially for fish species. This study proposes three novel mathematical models for competition between two fish populations, with control based on linear correlation feedback. The models consider different scenarios and purposes, including avoiding extinction of an inferior population, maximizing economic benefits, and preventing extinction due to unequal competition. The study provides effective control strategies and parameter optimization designs for these scenarios. Numerical simulations are conducted to demonstrate the theoretical results and feasibility of the control strategies. The findings contribute to our understanding of competition dynamics and provide insights for achieving coexistence in two-population systems.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Long-time behavior for impulsive generalized semiflows

Everaldo de Mello Bonotto, Piotr Kalita

Summary: We propose new criteria for the existence of global attractors for problems with state-dependent impulses that are more general than those previously known. Our results are applicable to both nonunique and unique solutions, and we provide collective versions of the criteria that demonstrate the upper-semicontinuity of global attractors under perturbation. The theory is illustrated through examples of ODEs and PDEs.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Passivity-based finite-region control of 2-D hidden Markov jump Roesser systems with partial statistical information

Feng Li, Zhenghao Ni, Lei Su, Jianwei Xia, Hao Shen

Summary: This paper addresses the problem of finite-region passive control for 2-D Markov jump Roesser systems, considering the partial statistical information issues on Markov parameters and transition probabilities. A 2-D hidden Markov model with partial statistical information is established to model this situation. The goal is to design a controller based on the 2-D hidden Markov model that ensures finite-time boundedness of both horizontal and vertical states of the 2-D Markov jump Roesser systems, while meeting a passive performance criterion. By employing the Lyapunov function method, criteria for the finite-region boundedness of 2-D Markov jump Roesser systems are developed, and a design method for the asynchronous controller based on the 2-D hidden Markov model is presented. The effectiveness of the proposed design method is validated through an illustrative example.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Compositional synthesis of control barrier certificates for networks of stochastic systems against w-regular specifications

Mahathi Anand, Abolfazl Lavaei, Majid Zamani

Summary: This paper proposes a compositional scheme for constructing control barrier certificates for interconnected discrete-time stochastic systems, which can synthesize switching controllers satisfying w-regular properties and provide probabilistic guarantees for specification satisfaction. The proposed scheme leverages interconnection topology and control sub-barrier certificates of subsystems to compositionally construct control barrier certificates of interconnected systems.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Practical exponential stability of impulsive stochastic functional differential systems with distributed-delay dependent impulses

Weijun Ma, Bo Yang, Yuanshi Zheng

Summary: This paper develops new practical stability criteria for impulsive stochastic functional differential systems with distributed-delay dependent impulses, and shows that under certain conditions, the practical exponential stability of the systems remains unchanged.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Lyapunov-based stability of time-triggered impulsive logical dynamic networks

Xueying Ding, Jianquan Lu, Xiangyong Chen

Summary: This paper investigates the stability of impulsive logical dynamic systems (ILDNs) from the perspectives of impulsive disturbance and impulsive control. The existing results on ILDN stability only consider a given impulsive instant sequence (IIS), which is restrictive. The paper proposes necessary and sufficient conditions for ILDN stability under any IIS by constructing a merged ILDN. However, these conditions are too strict as it is uncommon for a stable LDN to remain stable under any IIS. The paper introduces the concepts of impulsive disturbances and impulsive control, and presents sufficient conditions for LDN stability under time-triggered IISs with average impulsive interval. These results are also applied to set stability of ILDNs.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Asymptotic synchronization and topology identification of stochastic hybrid delayed coupled systems with multiple weights

Chunmei Zhang, Huiling Chen, Qin Xu, Yuli Feng, Ran Li

Summary: This article discusses a class of stochastic hybrid delayed coupled systems with multiple weights, and derives several conditions for asymptotic synchronization and topology identification of the systems based on Kirchhoff's Matrix-Tree Theorem and Lyapunov stability theory.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Minimum realization for controllability/observability of switched linear systems

Yan Zhu, Zhendong Sun

Summary: In this work, we address the minimum realization problem for controllability and observability of both continuous-time and discrete-time switched linear systems, and provide results for the tight upper bound.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Lyapunov conditions for exponential stability of nonlinear delay systems via impulsive control involving stabilizing delays

Weilian Liu, Xinyi He, Xiaodi Li

Summary: This paper investigates the problem of global exponential stability for nonlinear delay impulsive systems. By extending the traditional comparison principle and estimating the effects of delay on continuous and discrete dynamics, the internal relationship between delays, parameters of impulsive control, and continuous dynamics is revealed. Sufficient criteria for global exponential stability are obtained, quantitatively demonstrating the beneficial influences of delays on the system performance.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)

Article Automation & Control Systems

Global output feedback control for uncertain strict-feedback nonlinear systems: A logic-based switching event-triggered approach

Yanan Qi, Xianfu Zhang, Yanjie Chang, Rui Mu

Summary: This paper proposes a switching event-triggered approach to address the global output-feedback stabilization problem for a class of uncertain nonlinear systems. By using an event-triggered mechanism and a logic-based switching mechanism, the proposed approach determines the timing for sampling and switching control parameters, and develops an observer-based control scheme. With the ability to adaptively adjust the control parameter, this scheme has a stronger capability to handle large uncertainties, inherent nonlinearities, and sampling errors.

NONLINEAR ANALYSIS-HYBRID SYSTEMS (2024)