4.7 Article

Deterministic Learning-Based Adaptive Neural Control for Nonlinear Full-State Constrained Systems

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

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

Guohuai Lin et al.

Summary: This paper investigates the human-in-the-Ioop leader-following consensus control problem in multi-agent systems with unknown matched nonlinear functions and actuator faults. A neural fault-tolerant controller with dynamic coupling gains is proposed by using neural networks and fault estimators. It is proved that the state of each follower can synchronize with the leader's state and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed control method.

IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2022)

Article Automation & Control Systems

Adaptive Fault-Tolerant Tracking Control for Discrete-Time Multiagent Systems via Reinforcement Learning Algorithm

Hongyi Li et al.

Summary: This article investigates the adaptive fault-tolerant tracking control problem for a class of discrete-time multiagent systems via a reinforcement learning algorithm. The direct adaptive optimal controllers are designed by combining the backstepping technique with the reinforcement learning algorithm to reduce computational burden, and adaptive auxiliary signals are established to compensate for the influence of dead zones and actuator faults.

IEEE TRANSACTIONS ON CYBERNETICS (2021)

Article Computer Science, Artificial Intelligence

Low-Cost Approximation-Based Adaptive Tracking Control of Output-Constrained Nonlinear Systems

Kai Zhao et al.

Summary: A low-cost neuroadaptive tracking control solution is proposed for pure-feedback nonlinear systems under asymmetric output constraint. The solution is characterized by a novel output-dependent universal barrier function and a single parameter estimator, which ensure system stability and output constraint satisfaction.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Automation & Control Systems

Hamiltonian-Driven Hybrid Adaptive Dynamic Programming

Yongliang Yang et al.

Summary: This article introduces a model-based hybrid adaptive dynamic programming framework, including policy evaluation, improvement, and implementation steps, investigates the effect of sampling on communication bandwidth and control performance, shows a tradeoff between communication burden and performance, and demonstrates that developed policies exhibit Zeno behavior.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

Article Automation & Control Systems

Event-Triggered-Based Discrete-Time Neural Control for a Quadrotor UAV Using Disturbance Observer

Shuyi Shao et al.

Summary: The study utilizes an event-triggered-based neural control approach with a discrete-time disturbance observer to address control issues for quadrotor UAVs, effectively handling input saturation and external disturbances while ensuring bounded control signals.

IEEE-ASME TRANSACTIONS ON MECHATRONICS (2021)

Article Computer Science, Artificial Intelligence

Neural-Network-Based Event-Triggered Adaptive Control of Nonaffine Nonlinear Multiagent Systems With Dynamic Uncertainties

Hongjing Liang et al.

Summary: This article addresses the adaptive event-triggered neural control problem for nonaffine pure-feedback nonlinear multiagent systems with dynamic disturbance, unmodeled dynamics, and dead-zone input. The use of radial basis function neural networks to approximate unknown nonlinear functions and a dynamic signal to handle design difficulties in unmodeled dynamics were highlighted. A novel event-triggered control protocol was proposed to reduce communication burden and achieve convergence of follower outputs to a neighborhood of the leader's output, while ensuring bounded signals in the closed-loop system. An illustrative simulation example was provided to verify the efficacy of the proposed algorithms.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Finite-Time Tracking Control for Nonlinear Systems via Adaptive Neural Output Feedback and Command Filtered Backstepping

Lin Zhao et al.

Summary: This article presents a finite-time control strategy combined with neural networks and command filtered backstepping for the tracking control problem of uncertain high-order nonlinear systems with input saturation. The controller drives the output tracking error to the desired neighborhood of the origin at a finite time, and all signals in the closed-loop system are bounded at a finite time. Two simulation examples are provided to demonstrate the control effectiveness.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Automation & Control Systems

Time-varying IBLFs-based adaptive control of uncertain nonlinear systems with full state constraints

Lei Liu et al.

Summary: This paper presents an adaptive control design for nonlinear systems with time-varying full state constraints, which introduces novel TVIBLFs to overcome the conservatism existing in traditional methods and guarantee system stability and non-violation of constraint boundaries.

AUTOMATICA (2021)

Article Computer Science, Artificial Intelligence

Event-Triggered Fuzzy Bipartite Tracking Control for Network Systems Based on Distributed Reduced-Order Observers

Hongjing Liang et al.

Summary: This article addresses the issue of distributed observer-based event-triggered bipartite tracking control for stochastic nonlinear multiagent systems, proposing a novel approach with reduced-order observer and event-triggered mechanism. The designed bipartite tracking controller utilizes fuzzy logic systems and the backstepping approach, with theoretical proofs for its effectiveness. A simulation example is provided to demonstrate the effectiveness of the proposed scheme.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Distributed Cooperative Learning Control of Uncertain Multiagent Systems With Prescribed Performance and Preserved Connectivity

Shi-Lu Dai et al.

Summary: This article addresses the issue of distributed cooperative learning control for an uncertain high-order nonlinear multiagent system. The uncertain agent dynamics are estimated by localized radial basis function neural networks in a cooperative way, and an experience-based distributed controller is proposed to improve control performance.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

H∞ State Estimation for Neural Networks With General Activation Function and Mixed Time-Varying Delays

Wei Qian et al.

Summary: This article presents a method for H-infinity state estimation of neural networks with mixed delays, utilizing novel delay-product Lyapunov-Krasovskii functional with parameterized delay interval. By applying generalized free-weighting-matrix integral inequality and a more general activation function, a more accurate estimator model is obtained. The sufficient conditions derived confirm the asymptotic stability of the estimation error system with prescribed H-infinity performance.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Automation & Control Systems

The Set-Invariance Paradigm in Fuzzy Adaptive DSC Design of Large-Scale Nonlinear Input-Constrained Systems

Maolong Lv et al.

Summary: This paper introduces a novel adaptive dynamic surface control design for uncertain large-scale nonlinear systems without assuming continuous control gain functions. The design involves constructing invariant sets to remove the restrictive assumption of control gain function bounds and can handle input constraints like saturation. Semi-globally uniformly ultimate boundedness is proven through a combination of Lyapunov and invariant set theories.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

Article Automation & Control Systems

Modeling and trajectory tracking control for flapping-wing micro aerial vehicles

Wei He et al.

Summary: This paper studies the trajectory tracking problem of flapping-wing micro aerial vehicles in the longitudinal plane and proposes an adaptive control scheme to achieve autonomous flight. By designing position and attitude controllers, the effectiveness of the control scheme is discussed and verified through simulations.

IEEE-CAA JOURNAL OF AUTOMATICA SINICA (2021)

Article Computer Science, Information Systems

Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems

Lei Liu et al.

SCIENCE CHINA-INFORMATION SCIENCES (2020)

Article Computer Science, Information Systems

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

Hui Ma et al.

SCIENCE CHINA-INFORMATION SCIENCES (2020)

Article Automation & Control Systems

Adaptive Neural Command Filtering Control for Nonlinear MIMO Systems With Saturation Input and Unknown Control Direction

Jinpeng Yu et al.

IEEE TRANSACTIONS ON CYBERNETICS (2020)

Article Automation & Control Systems

L2-L∞ filtering for stochastic delayed systems with randomly occurring nonlinearities and sensor saturation

Wei Qian et al.

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE (2020)

Article Computer Science, Artificial Intelligence

Region Stabilization of Switched Neural Networks With Multiple Modes and Multiple Equilibria: A Pole Assignment Method

Liying Zhu et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

New optimal method for L2-L∞ state estimation of delayed neural networks

Wei Qian et al.

NEUROCOMPUTING (2020)

Article Automation & Control Systems

Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay

Da-Peng Li et al.

IEEE TRANSACTIONS ON CYBERNETICS (2019)

Article Computer Science, Information Systems

Backstepping Nussbaum gain dynamic surface control for a class of input and state constrained systems with actuator faults

Hamed Habibi et al.

INFORMATION SCIENCES (2019)

Article Automation & Control Systems

Adaptive Dynamic Surface Control Design for Uncertain Nonlinear Strict-Feedback Systems With Unknown Control Direction and Disturbances

Hui Ma et al.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2019)

Article Automation & Control Systems

Adaptive Fuzzy Control for Nonstrict-Feedback Systems With Input Saturation and Output Constraint

Qi Zhou et al.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017)

Article Automation & Control Systems

Dynamic Learning From Adaptive Neural Control of Robot Manipulators With Prescribed Performance

Min Wang et al.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017)

Article Automation & Control Systems

Adaptive Neural Control of Uncertain Nonstrict-Feedback Stochastic Nonlinear Systems with Output Constraint and Unknown Dead Zone

Hongyi Li et al.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017)

Article Automation & Control Systems

Adaptive Controller Design-Based ABLF for a Class of Nonlinear Time-Varying State Constraint Systems

Yan-Jun Liu et al.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017)

Article Engineering, Mechanical

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Hamed Habibi et al.

FRONTIERS OF MECHANICAL ENGINEERING (2017)

Article Automation & Control Systems

Adaptive neural control for a class of stochastic nonlinear time-delay systems with unknown dead zone using dynamic surface technique

Zifu Li et al.

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL (2016)

Article Automation & Control Systems

Cooperative control of a nonuniform gantry crane with constrained tension

Wei He et al.

AUTOMATICA (2016)

Article Automation & Control Systems

Neural Learning Control of Marine Surface Vessels With Guaranteed Transient Tracking Performance

Shi-Lu Dai et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2016)

Article Computer Science, Artificial Intelligence

Adaptive controller design-based neural networks for output constraint continuous stirred tank reactor

Dong-Juan Li et al.

NEUROCOMPUTING (2015)

Article Computer Science, Artificial Intelligence

Consensus-Based Distributed Cooperative Learning From Closed-Loop Neural Control Systems

Weisheng Chen et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

Adaptive Neural Output Feedback Control of Output-Constrained Nonlinear Systems With Unknown Output Nonlinearity

Zhi Liu et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

Learning From Adaptive Neural Dynamic Surface Control of Strict-Feedback Systems

Min Wang et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Information Systems

Dynamic learning from adaptive neural control with predefined performance for a class of nonlinear systems

Min Wang et al.

INFORMATION SCIENCES (2014)

Article Computer Science, Artificial Intelligence

Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems

Shi-Lu Dai et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)

Article Computer Science, Artificial Intelligence

Observer-Based Adaptive Neural Network Control for Nonlinear Stochastic Systems With Time Delay

Qi Zhou et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2013)

Article Computer Science, Theory & Methods

On the design of observer-based fuzzy adaptive controller for nonlinear systems with unknown control gain sign

A. Boulkroune et al.

FUZZY SETS AND SYSTEMS (2012)

Article Computer Science, Artificial Intelligence

Learning From ISS-Modular Adaptive NN Control of Nonlinear Strict-Feedback Systems

Cong Wang et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2012)

Article Automation & Control Systems

Control of nonlinear systems with time-varying output constraints

Keng Peng Tee et al.

AUTOMATICA (2011)

Article Automation & Control Systems

DETERMINISTIC LEARNING AND NONLINEAR OBSERVER DESIGN

Cong Wang et al.

ASIAN JOURNAL OF CONTROL (2010)

Article Computer Science, Artificial Intelligence

Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function

Beibei Ren et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2010)

Article Automation & Control Systems

Barrier Lyapunov Functions for the control of output-constrained nonlinear systems

Keng Peng Tee et al.

AUTOMATICA (2009)

Article Automation & Control Systems

Adaptive Backstepping Controller Design for Stochastic Jump Systems

Yuanqing Xia et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2009)

Article Computer Science, Artificial Intelligence

Learning from neural control

C Wang et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2006)

Article Automation & Control Systems

On designing of sliding-mode control for Stochastic jump systems

P Shi et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2006)

Article Automation & Control Systems

Dynamic surface control for a class of nonlinear systems

D Swaroop et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2000)