相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。
Article
Automation & Control Systems
Dong-Yang Jin et al.
Summary: This article addresses the problem of adaptive finite-time neural tracking control for nonstrict-feedback nonlinear systems. It proposes a new quasi-fast finite-time practical stability criterion and designs the desired controller using the dynamic surface technique and the structural feature of Gaussian functions. Simulation results demonstrate the effectiveness and practicability of the proposed design scheme.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Nan Wang et al.
Summary: This article investigates the problem of adaptive fuzzy control for stochastic high-order nonlinear systems with full-state constraints of the strict-feedback structure. A novel control strategy is proposed to solve this problem effectively.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Huifen Hong et al.
Summary: This paper studies the problem of leaderless fixed-time attitude consensus for rigid spacecraft systems, proposes a distributed control protocol based on the backstepping technique, and presents an adaptive fixed-time control for attitude consensus to remove the dependence of control gains on the global information. Unlike most existing consensus protocols, the parameters in the controllers for the spacecraft can be chosen independently and can be different from each other. The performances of the proposed control protocol are illustrated through a numerical simulation.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Theory & Methods
Xinfeng Shao et al.
Summary: This article studies the event-based adaptive practical fixed-time decentralized control problem for a class of large-scale uncertain nonlinear systems subject to non-affine nonlinear faults. By fusing the techniques of fixed-time control and command filter, the problems such as singular-value and computational explosion in fixed-time control based on backstepping design framework are solved. The proposed switching event-triggering mechanism provides greater flexibility in balancing system performance and network constraints.
FUZZY SETS AND SYSTEMS
(2022)
Article
Automation & Control Systems
Wenshun Lv et al.
Summary: In this paper, an adaptive neural control scheme is proposed for a class of unknown nonlinear systems with unknown sensor hysteresis. The scheme utilizes radial basis function neural networks to approximate the unknown nonlinearities and implements the backstepping technique to construct controllers. The control design is challenging due to the unavailability of genuine system states caused by sensor hysteresis. The proposed control scheme ensures practical finite-time stability of the closed-loop system, as proved by the Lyapunov theory. A numerical simulation example is provided to validate the effectiveness of the approach.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Xiaona Song et al.
Summary: This article investigates the issue of adaptive neural network fixed-time tracking control for a class of strict-feedback nonlinear systems with prescribed performance demands. By incorporating an improved fractional-order command filtered backstepping control technique and an event-driven-based fixed-time adaptive controller, the signals of the closed-loop system are practically fixed-time bounded and the tracking error is regulated.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Engineering, Electrical & Electronic
Qingtan Meng et al.
Summary: This paper investigates the problem of fixed-time stabilization for a class of nonlinear systems using event-triggered control. The event-triggered mechanism is applied to handle the coexistence of low-order and high-order nonlinearities in the system. By dividing the initial value of the system into two cases and designing an event-triggered controller for each case, the authors are able to deal with both low-order and high-order terms and achieve the objective of fixed-time stabilization. The paper proves the global fixed-time stability of the nonlinear system under the designed controller using switching control theory, while excluding the occurrence of Zeno behavior. The effectiveness of the proposed technology is demonstrated through two simulations.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2022)
Article
Computer Science, Artificial Intelligence
Xiang Zhang et al.
Summary: Based on the interval type-2 fuzzy approach, this article investigates the fault detection filter design problem for a class of nonhomogeneous higher level Markov jump systems with uncertain transition probabilities. The proposed asynchronous IT2F filter, utilizing hidden Markov model and Gaussian transition probability density function, can effectively detect faults without error alarms, as verified by the simulation study on a quarter-car suspension system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Yingjie Deng et al.
Summary: This paper presents a new approach to control nonstrict-feedback nonlinear systems using a single approximator (neural network or fuzzy logic system) in the first step of backstepping, ensuring computational simplicity. The bounded property of basis functions solves the algebraic loop problem, and the double-channel event-triggered control ensures closed-loop stability.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Peng He et al.
Summary: In this paper, a self-triggered model predictive control (MPC) strategy is proposed for discrete-time semi-Markov jump linear systems to achieve a desired finite-time performance. By introducing the concept of multi-step semi-Markov kernel, the multi-step predictive states under system mode jumping are obtained. Meanwhile, a self-triggered scheme is used to automatically predict sampling instants and reduce the computational burden of on-line solving of MPC.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Yixuan Yuan et al.
Summary: This paper focuses on fast finite time stability for a class of stochastic nonlinear systems. Firstly, a useful inequality based on Bihari inequality, which plays a crucial role in fast finite time stability in probability, is expanded. Then, the concept of fast finite time stability is discussed for stochastic nonlinear systems, and an important theory related to fast finite time stability in probability is obtained. Next, a subtle design of a fast finite time state feedback controller is proposed, which achieves not only the reduction of convergence time but also the minimization of control effort. Three simulation examples are provided to support the theoretical analysis results.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Mathematics, Applied
Issam El Hamdi et al.
Summary: This paper investigates the robust second-moment stability of stochastic linear systems with varying delays, presenting a condition for checking system stability based on uncertain parameters within a polytope. Due to the difficulty in numerically checking the spectral radius, a randomized approach is proposed to improve the accuracy and practicality of stability verification. A real-time electronic application is used to demonstrate the potential benefits of the proposed method.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Information Systems
Xin Jin et al.
Summary: This article investigates the fuzzy adaptive control design for a class of stochastic nonstrict feedback nonlinear systems, introducing a bounded estimation method, smooth functions, and barrier Lyapunov functions to ensure the controlled system's performance and stability. The proposed asymptotic tracking control scheme shows superior performance in an illustrative simulation instance.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Guozeng Cui et al.
Summary: This paper investigates finite-time adaptive fault-tolerant tracking control for nonstrict-feedback nonlinear systems by introducing a novel finite-time command filter and a fractional order error compensation mechanism. A control strategy combining neural networks and command filtered backstepping approach is established to ensure output tracking error convergence within finite-time and bounded closed-loop system signals. Simulation examples are provided to verify the effectiveness of the proposed method.
INFORMATION SCIENCES
(2021)
Article
Engineering, Electrical & Electronic
Huanqing Wang et al.
Summary: This paper investigates fuzzy-based adaptive event-triggered tracking control for a class of non-strict-feedback nonlinear systems within fixed-time interval. Fuzzy logic system approximates unknown nonlinearities, event-triggered mechanism schedules data transmission dependent upon errors exceeding threshold. A fuzzy-based adaptive event-triggered controller is developed using backstepping design algorithm and Lyapunov stability theorem, ensuring singularity problem elimination, boundedness of closed-loop signals, and tracking error convergence.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
Article
Automation & Control Systems
Wei Su et al.
Summary: This article introduces an adaptive intelligent asymptotic tracking control method for a class of stochastic nonlinear systems with unknown control gains and full state constraints. By utilizing an auxiliary virtual controller and new mathematical methods, the technical difficulties arising from unknown control gains are overcome. Additionally, a new control method is proposed by combining neural networks and gain suppression technology, which is validated through simulation results.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Wengui Yang et al.
Summary: This article investigates a class of uncertain nonstrict-feedback fractional-order nonlinear single-input-single-output systems using fuzzy-logic systems to approximate unknown nonlinear functions. Adaptive fuzzy state-feedback control scheme is developed for measurable states and observer-based output-feedback control design is proposed for unmeasurable states. The proposed control approaches are validated with numerical simulations demonstrating semiglobally uniformly ultimate boundedness and tracking errors convergence to a small neighborhood of the origin.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Automation & Control Systems
Yekai Yang et al.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2020)
Article
Automation & Control Systems
Hang Su et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Automation & Control Systems
Fei Shen et al.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2020)
Article
Automation & Control Systems
Zifu Li et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Automation & Control Systems
G. Yu. Kulikov et al.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2019)
Article
Automation & Control Systems
Yongming Li et al.
Article
Automation & Control Systems
Toshio Yoshimura
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2018)
Article
Automation & Control Systems
Lantao Xing et al.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2017)
Article
Automation & Control Systems
Xudong Zhao et al.
Article
Computer Science, Artificial Intelligence
Yan-Jun Liu et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2015)
Article
Automation & Control Systems
Andrey Polyakov
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2012)
Article
Computer Science, Artificial Intelligence
Shaocheng Tong et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2012)
Article
Engineering, Mechanical
Yue Li et al.
NONLINEAR DYNAMICS
(2012)
