Article
Automation & Control Systems
Wanmin Chang, Yongming Li, Shaocheng Tong
Summary: An adaptive fuzzy state feedback control method is proposed for a single-link robotic manipulator system with unknown nonlinear function and actuator saturation. The method uses fuzzy logic systems and a smooth function to approximate the unknown nonlinearities and actuator saturation. By combining command-filter technique with backstepping design algorithm, a novel control method is developed to guarantee stability and output tracking performance of the system.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Automation & Control Systems
Haochen Zhang, Aiguo Song, Huijun Li, Shaobo Shen
Summary: Two novel adaptive finite-time control schemes are proposed for position tracking of nonlinear teleoperation system, considering dynamic uncertainties, actuator saturation, and time-varying communication delays. The control schemes involve the use of auxiliary variables, RBF neural networks, gain switching strategies, and compensation adaptive update laws in dealing with saturation. The effectiveness of the proposed control schemes is demonstrated through simulation experiments.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Engineering, Electrical & Electronic
Guoshun Cai, Liwei Xu, Ying Liu, Jiwei Feng, Jinhao Liang, Yanbo Lu, Guodong Yin
Summary: This paper addresses the uncertainties and disturbances in the path tracking control of autonomous vehicles (AVs) by using preview control theory. It considers unmeasureable multi-uncertainties and external disturbance, handles time-varying system delays, and considers physical constraints for practical implementation. The proposed controller design is formulated as an optimization problem based on linear matrix inequalities (LMIs) using convexification techniques.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Wei Sun, Shuzhen Diao, Shun-Feng Su, Zong-Yao Sun
Summary: This study proposes a fixed-time tracking control scheme to address the control problem for nonlinear systems subject to actuator saturation. The scheme improves the controller performance by approximating the saturation function and introducing an auxiliary system. The effectiveness of the proposed method is demonstrated through theoretical analysis and numerical examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
K. Udhayakumar, S. Shanmugasundaram, Ardak Kashkynbayev, R. Rakkiyappan
Summary: This article focuses on the projective synchronization problem of a class of nonlinear discontinuous coupled inertial neural networks with mixed time-varying delays and a cluster topological structure. The required conditions for network convergence under the influence of a wide range of impulses are determined using matrix measure technique and average impulsive intervals. Numerical simulations are used to provide graphical representations of varied impulsive ranges for multiple cases.
Article
Computer Science, Artificial Intelligence
Hong Cheng, Xiucai Huang, Hongwei Cao
Summary: This paper proposes a method to achieve asymptotic tracking control for uncertain nonlinear strict-feedback systems with unknown time-varying delays and unknown control direction. The Lyapunov-Krasovskii functional is used to deal with the time delays, and the neural network is applied to compensate for the unknown terms arising from the derivative of the Lyapunov-Krasovskii functional. An NN-based adaptive control scheme is constructed based on backstepping technique, and the output tracking error is ensured to converge to zero asymptotically. The proposed method settles the singularity issue commonly encountered in coping with time delay problems and improves the transient performance with proper choice of design parameters.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Wei Sun, Jing Wu, Shun-Feng Su, Xudong Zhao
Summary: This study proposes a solution to the fixed-time tracking control problem for nonlinear systems with quantized inputs and actuator faults. By using neural networks to approximate unknown nonlinear function terms and employing adaptive estimations and innovative design signals, the proposed control algorithm compensates for the influence of actuator faults and quantized inputs. Theoretical analysis shows that the proposed scheme ensures the output tracking error converges to a small neighborhood of the origin within a fixed time, and the upper bound of the setting time can be preassigned.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
K. Udhayakumar, S. Shanmugasundaram, Ardak Kashkynbayev, K. Janani, R. Rakkiyappan
Summary: This paper explores the synchronization of inertial neural networks (INNs) with time-varying delay and coupling delays using control systems with saturated and asymmetrically saturated impulses. Theoretical discussions introduce mixed delays for INNs, and the addressed model is transformed into first-order differential equations using variable transformation and dead-zone function. Adequate conditions for exponential synchronization are derived, and an asymmetric saturated impulsive control approach is proposed for achieving exponential synchronization in the leader-following synchronization pattern of INNs. Simulation results validate the theoretical findings.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Automation & Control Systems
Yinghong Zhao, Yangfan Liu, Yuechao Ma
Summary: This paper addresses the finite-time bounded issue for discrete-time singular time-varying delay system using sliding mode control method, presenting suitable control law and solving method. The superiority and practicality of the results are demonstrated through numerical examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Mathematics, Applied
Yuzhen Chen, Haoxin Liu, Rui Dong
Summary: This paper proposes a new method to address the stabilization problem of uncertain saturated linear systems with multiple discrete delays. By constructing a new type of Lyapunov-Krasovskii functional and incorporating integral inequalities, stabilization and robust stabilization conditions are derived.
Article
Engineering, Electrical & Electronic
Khadija Naamane, El Houssaine Tissir
Summary: This paper presents a robust anti-windup compensator methodology for stabilizing nonlinear time-varying delay systems described by Takagi-Sugeno fuzzy models. By developing an anti-windup control approach based on Lyapunov-Krasovskii functional and delay-dependent analysis, sufficient conditions for robust stabilization via anti-windup controller are derived. An algorithm is provided to optimize the anti-windup gain and reduce conservatism, with numerical examples demonstrating the effectiveness and improvements over existing methods.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Information Systems
Shiv Shankar Chouhan, Rakesh Kumar, Shreemoyee Sarkar, Subir Das
Summary: This article studies the multistability analysis of n-dimensional octonion valued neural networks (OVNNs) with time-varying delays for a general class of activation functions. The OVNNs are decomposed into eight real-valued systems, and 38n disjoint regions are constructed in On based on geometric properties of the activation functions. By using the inequality technique, several sufficient conditions are obtained to ensure the existence of 38n equilibrium points, with 28n of them being locally exponentially stable. Furthermore, the article estimates positively invariant sets and provides numerical examples to illustrate the effectiveness of the obtained results, particularly in storing and retrieving true-color images.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Yongchao Liu, Qidan Zhu
Summary: In this article, an event-triggered adaptive neural network (ANN) control strategy is developed for stochastic nonlinear systems with state constraints and time-varying delays. The state constraints are handled using the barrier Lyapunov function, and neural networks are utilized to identify unknown dynamics. The use of the Lyapunov-Krasovskii functional helps counteract the adverse effects of time-varying delays. The controller design incorporates the backstepping technique and event-triggered mechanism (ETM) to minimize data transmission and save communication resources.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Mathematics, Applied
Zahra Sadat Aghayan, Alireza Alfi, J. A. Tenreiro Machado
Summary: This article investigates the stability of uncertain fractional order systems of neutral type under actuator saturation, and constructs criteria for asymptotic robust stability with the Lyapunov-Krasovskii functional. A state-feedback control law is formulated using linear matrix inequalities, and an algorithm for determining the controller gain is provided via the cone complementarity linearization method. The main results are illustrated through numerical examples.
COMPUTATIONAL & APPLIED MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Yin Wang, Shutang Liu, Xiang Wu
Summary: This study addresses the synchronization problem of two fractional reaction-diffusion neural networks with input saturation and time-varying delays using the Lyapunov direct method. By introducing a novel definition of the ellipsoid and linear region of the saturated, the traditional ellipsoid method is extended, making the approach concise and effective. Through the utilization of a new Lyapunov-Krasovskii functional, synchronization criteria are established and the domain of attraction is estimated, with all results presented in the form of linear matrix inequalities (LMIs).
Article
Automation & Control Systems
Ruiming Xie, You Wu, Xue-Jun Xie
Summary: This paper proposes a practical preassigned finite-time tracking control scheme for state-constrained high-order nonlinear systems, using fuzzy systems to eliminate the need for growth assumptions on completely unknown nonlinearities. By integrating nonlinear transformed functions with key coordinate transformations into control design, the system is able to handle full-state constraints and ensure that the tracking error converges to a small region around zero in a preassigned finite time. Simulation examples demonstrate the effectiveness and advantages of this control scheme.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Wenjing Hou, You Wu, Xue-Jun Xie
Summary: This paper investigates the adaptive finite-time stabilisation for a class of output-constrained low-order nonlinear systems with unknown time-varying powers, parametric and dynamic uncertainties. It proposes a unified adaptive state-feedback controller that can handle both constrained and unconstrained systems by characterising unmeasured dynamic uncertainty, applying finite-time stability theory, and introducing specific Lyapunov functions. The simulation example demonstrates the effectiveness of the proposed control scheme.
INTERNATIONAL JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
You Wu, Xue-Jun Xie
Summary: This article introduces an adaptive state-feedback controller for the stability of nonlinear systems with unknown time-varying powers and full-state constraints. By incorporating new concepts and methods, it is proven that the signals of the closed-loop system are bounded and the system states converge to a small region around zero.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Yaping Tang, Weiwei Sun, Dongqing Liu
Summary: This paper focuses on the simultaneous exponential stabilization of a set of stochastic port-controlled Hamiltonian (PCH) systems. The paper considers the limited bandwidth of channels, fading channels, transmission delays, and actuator saturation constraint. Sufficient criterions are given for controller design based on dissipative Hamiltonian structural and saturating actuator properties.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Gaoran Wang, Weiwei Sun
Summary: This paper investigates the output tracking problem of Hamiltonian descriptor systems under the influence of saturation and time delay. An extended composite nonlinear feedback (ECNF) control method is proposed to achieve fast output tracking and reduce tracking overshoot. By considering the special form of the Hamiltonian descriptor system and using model transformation, the closed-loop Hamiltonian descriptor system is replaced by two subsystems without singularity for easier processing. Criteria for asymptotic output tracking of closed-loop Hamiltonian descriptor systems are obtained for two different types of time delays. The effectiveness of the ECNF method is tested using practical and numerical examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
You Wu, Xue-Jun Xie, Zeng-Guang Hou
Summary: This article discusses an adaptive fuzzy asymptotic tracking control method for high-order nonlinear time-delay systems with full-state constraints. Utilizing fuzzy-logic systems and a separation principle to relax growth assumptions on unknown nonlinearities, the study successfully achieves asymptotic tracking and validates the effectiveness of the method through two examples.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Mathematics, Interdisciplinary Applications
Fan Liu, You Wu
Summary: This paper focuses on the adaptive event-triggered finite-time tracking problem of output-constrained high-order nonlinear systems with time-varying powers. By introducing nonlinear mappings, finite-time performance functions, and low-power and high-power terms, an adaptive state-feedback controller is designed to eliminate the effects caused by the output constraint and time-varying powers. Simulation examples demonstrate the effectiveness of this control scheme.
Article
Automation & Control Systems
You Wu, Wenjing Hou
Summary: This paper investigates the adaptive state-feedback stabilization for a class of output-constrained high-order nonlinear systems with integral input-to-state stability (iISS) inverse dynamics. By integrating different functions and parameter update laws, a unified adaptive state-feedback controller is constructed, which can handle both constrained and unconstrained systems. It is proven that the closed-loop signals are bounded, the symmetric output constraint is not violated, and system states converge to zero asymptotically.
INTERNATIONAL JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Weiwei Sun, Xinyu Lv, Mengyang Qiu
Summary: This article introduces a distributed estimator design problem for stochastic Hamiltonian systems under fading wireless channels. The goal of the problem is to design estimators that can estimate the target state of the Hamiltonian system and ensure the stability of the estimation system using fading channels and graph theory. The article provides sufficient conditions for the existence of the designed estimator gain for each sensor and validates the theoretical claims through two examples.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Qi Zhang, Weiwei Sun, Chaoqian Qiao
Summary: This paper presents a Hamiltonian approach to study the event-triggered stabilisation problem of switched affine nonlinear systems with actuator saturation. The proposed strategy can ensure the asymptotic stability of the plant without violating actuator saturation, even if there exists asynchronous phenomenon between the subsystems and their candidate controllers. This extends available results for switched nonlinear systems and reduces energy consumptions.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Gaoran Wang, Weiwei Sun, Lusong Ding
Summary: In this study, a novel cooperative control strategy is proposed to address the time-delayed wind power grid-connected unit and actuator saturation constraints. The system is transformed into a Hamiltonian structure, and a passive controller is designed to ensure stability. Furthermore, an output feedback synchronous controller is proposed to handle the saturation problem when multiple grids are connected in parallel. The simulation results verify the effectiveness of the proposed control strategy.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Dehai Yu, Weiwei Sun, Xiangyu Chen, Mingyuan Du
Summary: This paper addresses the problem of anti-saturation control in a permanent magnet synchronous wind power system. A new coordination controller is designed using adaptive sliding mode control and port-controlled Hamiltonian (PCH) control methods, which effectively handles input saturation and compensates for system model uncertainties. The coordination controller employs an exponential function with adjustable parameters as the coordination function, enabling faster response to input saturation and improved dynamic performance. Simulation results demonstrate the effectiveness of the proposed strategy and comparison with traditional control approaches is provided. The proposed strategy enables speed tracking control of the generator and enhances the wind energy capture of the wind turbine for improved wind energy utilization.
