Article
Automation & Control Systems
Xiandong Chen, Xianfu Zhang, Chunjiang Qian
Summary: This article proposes a control strategy for the fixed-time stabilization problem of high-order nonlinear systems with monotone degrees and output constraints, utilizing a novel Lyapunov function and AAPI technique to achieve stable control while meeting state constraints. The novelty of this strategy lies in its ability to simultaneously address systems with and without output constraints without altering the controller structure. A simulation example demonstrates the effectiveness of the proposed control strategy.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Jiali Ma, Shumin Fei, Shengyuan Xu
Summary: This article addresses the global fixed-time stabilization problem for a class of switched uncertain nonlinear systems. A novel adaptive controller is proposed, and a dynamic controller parameter is introduced to cope with the unknown system parameters. An effective common regulate rule is designed based on the improved fixed-time stability framework. It is shown that the controller parameter can be regulated online to compensate the unknown system parameters and achieve fixed-time convergence to zero under arbitrary switchings.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Zhibao Song, Ping Li
Summary: This paper proposes a novel universal barrier Lyapunov function for fixed-time stabilization of switched stochastic nonlinear systems with asymmetric output constraints. By adding a power integrator strategy, an elaborate control method is established to ensure system state fixed-time convergence to zero and maintain system output within the preset asymmetric region.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Automation & Control Systems
Lei Wang, Keqi Mei, Shihong Ding
Summary: This paper addresses the design of a fixed-time controller for second-order sliding mode dynamics with asymmetric output constraints. By constructing a barrier Lyapunov function and adding a power integrator, a fixed-time SOSM controller is developed to handle the asymmetric output constraint issue, ensuring the sliding variable converges to the origin within a fixed time and the system output never violates the asymmetric constrained area boundary. Two examples are provided to verify the effectiveness and feasibility of the proposed scheme.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Mechanical
Chih-Chiang Chen, Zong-Yao Sun
Summary: This article studies the fixed-time stabilization problem for a class of uncertain high-order nonlinear systems with an asymmetric output constraint. A tangent-type barrier function is developed as an intermediate design ingredient, and the intrinsic attributes of signum functions are utilized to renovate the technique of adding a power integrator. This approach enables the construction of a tangent-type asymmetric barrier Lyapunov function and a continuous state feedback fixed-time stabilizer while guaranteeing the achievement of pre-specified output constraints.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Yaowei Sun, Jun Zhao
Summary: This paper studies the problem of finite-time control for switched nonlinear systems, introducing the notion of finite-time as a performance index and deriving a sufficient condition for solving the finite-time control problem using the method of multiple Lyapunov functions and the technique of adding a power integrator. The effectiveness of the provided control strategy is demonstrated through a simulation example.
INTERNATIONAL JOURNAL OF CONTROL
(2021)
Article
Automation & Control Systems
Dawei Wu, Yonghui Sun, Shuyi Shao
Summary: A new framework of robust adaptive neural control for nonlinear switched stochastic systems is proposed in the presence of external disturbances and system uncertainties. An improved model-dependent average dwell time (MDADT) method is developed, and a switched disturbance observer and processing method are designed for real-time gain adjustment and continuity of control law. Theoretical proof guarantees the boundedness of all closed-loop signals, and simulation results further confirm the effectiveness of the proposed framework.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Yanxian Chen, Zhi Liu, C. L. Philip Chen, Yun Zhang
Summary: This paper proposes a novel mode-dependent fuzzy fixed-time controller to compensate for uncertain deadzone in the adaptive fixed-time control of switched systems. The proposed controller overcomes the difficulty of constructing a fixed-time controller in the presence of a complicated switched network topology and deadzone input. The stability analysis and simulation examples confirm the feasibility of the presented design.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Fenglan Wang, Lijun Long
Summary: This paper investigates the problem of event-triggered adaptive neural network control for multi-input multi-output switched nonlinear systems with output and state constraints and noninput-to-state practically stable unmodeled dynamics. The paper proposes a nonlinear mapping to handle constraints, overcomes the difficulty caused by some non-ISpS unmodeled dynamics with a new switching signal, and designs event-triggering mechanisms and adaptive neural network controllers to deal with asynchronous switching without any known restriction on maximum asynchronous time.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Keqi Mei, Shihong Ding, Chih-Chiang Chen
Summary: This study proposes a novel fixed-time control scheme for nonlinear systems with output constraints, in which the upper bound of settling time can be estimated independently of initial states and the output constraint is handled through a barrier Lyapunov function. The proposed controller ensures fixed-time stability and avoids violating the preset output constraint.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Computer Science, Information Systems
Feiyue Wu, Jie Lian, Dong Wang
Summary: This paper investigates the constrained stabilization problem of switched positive linear systems (SPLS) with bounded inputs and states using the set-theoretic framework of polyhedral copositive Lyapunov functions (PCLFs). It is shown that the existence of a common PCLF is necessary and sufficient for the stabilizability of an SPLS, and a PCLF-based approach is proposed for stabilization with a larger estimate of the domain of attraction for the constrained SPLSs. The analysis problems are converted into optimization problems with linear matrix inequalities as constraints when certain variables are fixed.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Liandi Fang, Shihong Ding, Ju H. Park, Li Ma
Summary: This article proposes an adaptive fuzzy control algorithm for high-order lower triangular nonlinear systems with output constraints and unknown nonlinearities. The algorithm combines a constructed barrier Lyapunov function (BLF) and a power integrator technique to ensure the boundedness of all variables in the closed-loop system in probability. Comparative simulation results demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Engineering, Mechanical
Zhi Fan, Yongchun Fang, Yinan Wu, Cunhuan Liu
Summary: Hybrid systems, due to the interaction of different sub-systems, are more complex and challenging to design stable controllers for. The traditional approach of designing controllers for each sub-system separately does not consider the switches between sub-systems, resulting in poor or even unstable performance. This paper proposes a control scheme that takes into account the system's switching behaviors to design suitable controllers for hybrid systems and achieve overall stability. The scheme consists of two steps, resulting in guaranteed stability and closed-loop performance.
NONLINEAR DYNAMICS
(2022)
Article
Mathematics, Applied
Xuhuan Wang, Youhua Peng, Yuande Xie
Summary: In this paper, the problem of fixed-time stabilization (FTS) for a class of second-order nonlinear time-delay systems is investigated. A design scheme of fixed-time stability for time-delay systems based on fixed-time stability theory and Lyapunov-Krasovskii functional is proposed. This scheme effectively solves the adverse impact of time-delay on the system and ensures the stability of the corresponding closed-loop system for a fixed time. The proposed control methods attenuate the influences of time-delay state and nonlinear uncertainties through feedback methods. The effectiveness of the design scheme is demonstrated through simulations.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Automation & Control Systems
Fazhan Tao, Pengyu Fan, Zhumu Fu, Nan Wang, Yueyang Wang
Summary: An adaptive fuzzy fixed time control scheme is developed for stochastic pure-feedback nonlinear systems with full state constraints in this paper. The proposed scheme guarantees the boundedness and convergence of all signals in the systems within a fixed time, as verified by simulation examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control 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.
Article
Engineering, Electrical & Electronic
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
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
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
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
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
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.
Article
Computer Science, Artificial Intelligence
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
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
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
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.
Article
Computer Science, Information Systems
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
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.
Article
Engineering, Electrical & Electronic
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
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
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
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
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
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
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
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
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
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
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
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
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)