检索结果-内蒙古大学图书馆

Adaptive Fault Tolerant Consensus Tracking Control for Flexible Manipulators MASs With input quantization and Time-Varying Delay

引用

IEEE TRANSACTIONS ON CYBERNETICS 2025年第6期55卷 2597-2607页

作者： Zhao, Wei Li, Xing Liu, Yu Li, Zhijun South China Univ Technol Sch Automat Sci & Engn Guangzhou 510640 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind SAPI Shenyang 110819 Peoples R China Dongguan Univ Technol Sch Elect Engn & Intelligentizat Dongguan 523808 Peoples R China Tongji Univ Sch Mech Engn Shanghai 200092 Peoples R China Shanghai Key Lab Wearable Robot & Human Machine In Shanghai 201804 Peoples R China

This article mainly investigates the problem of vibration suppression and angle cooperative tracking control of a multiple flexible manipulators described by partial differential equations (PDEs) with input quantization, actuator failures, and unmodeled system dynamics. An intermediate control law is designed, and a smooth function with a positive integrable time-varying function is introduced. Besides, a new smooth function is constructed in the control law to handle the influence of quantization and actuator faults. Under the designed controller, the angles of all flexible manipulators can reach consensus through mutual communication, and the elastic deformation of each flexible manipulator can also be suppressed. Furthermore, the asymptotic stability of a closed-loop system is realized based on the Lyapunov function. Finally, numerical simulation validates the effectiveness of the method.

关键词： quantization (signal) Vibrations Fault tolerant systems Fault tolerance Adaptive systems Actuators Manipulator dynamics Fuzzy logic Consensus control Adaptive control Actuator faults consensus tracking control distributed parameter system input quantization vibration suppression

来源：评论

学校读者我要写书评

暂无评论

Adaptive Neural Fault Tolerant Control for input-Delayed Stochastic Systems Subject to States and input quantization

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第4期55卷 2451-2462页

作者： Wu, Jian Yang, Yadong Chen, Weisheng Wang, Hai Wu, Zheng-Guang Anqing Normal Univ Univ Key Lab Intelligent Percept & Comp Anhui Prov Anqing 246133 Peoples R China Xidian Univ Sch Aerosp Sci & Technol Xian 710071 Peoples R China Murdoch Univ Harry Butler Inst Perth WA 6150 Australia Zhejiang Univ Inst Cyber Syst & Control Natl Lab Ind ControlTechnol Hangzhou 310027 Peoples R China

For the input-delayed stochastic systems with the states and input quantization, the adaptive stabilization problem is investigated in this article. The whole control scheme design process can be divided into three steps. First, the traditional adaptive neural control scheme is developed for the controlled system. Next, the effective control scheme is proposed for the system with the quantized states. Finally, the adaptive neural control method is developed for the considered system with the states and input quantization. The radial basis function neural network (RBFNN) is applied to approximate the unknown terms online, and the Pade approximation method is introduced to deal with the input-delayed problems. The adaptive neural fault control strategy is presented to address sensor faults and the discontinuity due to the quantized states. Under the constructed controllers, all the closed-loop signals remain semi-globally uniformly ultimately bounded (SGUUB) in mean square. The effectiveness and superiority of the presented control schemes are verified by some simulation results.

关键词： input delay input quantization quantized states sensor faults stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Event-triggered anti-disturbance trajectory tracking for under-actuated surface vehicle under multiple constraints and input quantization

引用

OCEAN ENGINEERING 2025年 329卷

作者： Yue, Yuanning Ning, Jun Hu, Xin Li, Wei Dalian Maritime Univ Coll Nav Dalian 116026 Peoples R China Liaoning Key Lab Marine Emergency Technol Dalian 116026 Peoples R China Ludong Univ Sch Math & Stat Sci Yantai 264025 Peoples R China

In this paper, a disturbance observer based trajectory tracking control method for under-actuated surface vehicle (USV) is investigated with multiple constraints. In light of the intricate constraints encountered by the USV system, such as input, output, and execution constraints of the under-actuated USV, this research suggests a novel control approach. A disturbance observer compensates for the impacts of external disturbances on the control system and estimates them efficiently. Surge controllers and yaw controllers are designed to address the issue of under-actuated USV with two configurable inputs: yaw moment and surge control force. The saturation function and Barrier Lyapunov function are used to solve the input and output constraints of the under-actuated USV, ensuring that the system's state and control in-puts remain within an acceptable range. The input quantization technique and the time-varying threshold event-triggered mechanism are introduced in this study to further reduce the energy consumption and communication overhead. Ultimately, this study uses simulation and stability analysis to confirm the efficacy of the suggested approach, and the findings demonstrate that the control strategy can sustain accurate trajectory tracking performance while adhering to the constraints.

关键词： Under-actuated unmanned surface vehicle Trajectory tracking control Disturbance observer Multiple constraints input quantization Event-triggered mechanism

来源：评论

学校读者我要写书评

暂无评论

A composite filter-based approach to adaptive prescribed-time output-feedback control of strict-feedback nonlinear systems with output and input quantization

引用

APPLIED MATHEMATICS AND COMPUTATION 2025年 494卷

作者： Chen, Chen Li, Jinghao Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

This paper investigates the adaptive prescribed-time control problems of strict-feedback nonlinear systems with output quantization, input quantization and unknown control coefficients. Firstly, a quantized K-filter is constructed to estimate the system states. Then, a set of command filters are introduced to smooth the discontinuous stabilizing functions and reduce the computational burden. Moreover, a class of scaling functions are designed to achieve the desired prescribed- time tracking performance. Based on the quantized K-filter, a set of command filters and a class of scaling functions, a set of new error variables are established to facilitate the design of the quantized composite filter-based adaptive prescribed-time control method. It is proved that the tracking error converges to an adjustable compact set within a prescribed time. Finally, two examples are provided to illustrate the effectiveness of the proposed method.

关键词： Command filtered adaptive backstepping input quantization K-filter Output quantization Prescribed-time control

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Trajectory Tracking Control of Under-Actuated Unmanned Surface Vehicles With Ocean Current and input quantization

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第1期55卷 63-72页

作者： Ning, Jun Wang, Yu Wang, Eryue Liu, Lu Philip Chen, C. L. Tong, Shaocheng Dalian Maritime Univ Coll Nav Dalian 116026 Peoples R China Dalian Maritime Univ Sch Marine Elect Engn Dalian 116026 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Liaoning Inst Technol Dept Math Jinzhou 121001 Peoples R China

This article focuses on the trajectory tracking control of under-actuated unmanned surface vehicles subject to unknown ocean current and input quantization. Regarding kinematics, we devise an extended-state-observer-based guidance law capable of compensating for ocean currents to track the intended trajectory. Concerning kinetics, we propose an event-triggered adaptive fuzzy quantization control law using a linear analytical model to depict input quantization, eliminating the need for prior quantization parameter information. A notable aspect is the reduction in both execution frequency and magnitude, thereby mitigating communication burdens. The stability of this control strategy is proofed through input-to-state stability analysis. Simulation experiments are conducted to affirm the viability of the event-triggered adaptive fuzzy quantization control strategy.

关键词： Event-triggered mechanism extended state observer fuzzy adaptive control input quantization ocean current unmanned surface vehicles (USVs)

来源：评论

学校读者我要写书评

暂无评论

Integral Reinforcement Learning Control of an Uncertain 2-DOF Helicopter System With input quantization and State Constraints

引用

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2025年

作者： Zhao, Zhijia Weng, Yan Liu, Zhijie Liu, Yu Hong, Keum-Shik Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China Univ Sci & Technol Beijing Inst Artificial Intelligence Beijing 100083 Peoples R China Univ Sci & Technol Beijing State Key Lab Adv Met Beijing 100083 Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou 510640 Peoples R China Qingdao Univ Inst Future Sch Automat Qingdao 266071 Peoples R China Pusan Natl Univ Sch Mech Engn Busan 46241 South Korea

This study presents an integral reinforcement learning (RL) control strategy for an uncertain two-degree-of- freedom (2-DOF) helicopter system by considering the input quantization and state constraints. Initially, a hysteresis quantizer is utilized to reduce oscillations when transmitting input signals. Within the control framework, the model uncertainty is estimated by an action neural network (NN), while the long-term cost function is approximated by a critic NN. Moreover, integral barrier Lyapunov functions (IBLFs) are employed to directly restrict the states, thereby guaranteeing the convergence of the helicopter system. Lyapunov stability theory demonstrates that all signals within the closed-loop system are semiglobal uniform ultimate bounded. Ultimately, the efficacy of the proposed control strategy is validated via both simulations and experiments.

关键词： quantization (signal) Helicopters Artificial neural networks 2-DOF Uncertainty Control systems Hysteresis Lyapunov methods Convergence Adaptive systems input quantization integral barrier Lyapunov function (IBLF) integral reinforcement learning (RL) control neural network (NN) two-degree-of-freedom (2-DOF) helicopter system

来源：评论

学校读者我要写书评

暂无评论

Adaptive fixed-time containment control of underactuated surface vessels with input quantization

引用

OCEAN ENGINEERING 2025年 318卷

作者： Yan, Yan Yin, Changtong Hou, Yanqing Yu, Shuanghe Liu, Yi Dalian Maritime Univ Coll Marine Elect Engn Dalian 116026 Peoples R China

This article investigates the fixed-time containment control problem for multi-underactuated surface vessels (USVs) subject to input quantization. By selecting a hand position point, the underactuated problem of the vessels is removed. Based on this, a novel adaptive law is incorporated into the containment control scheme to tackle external disturbances and input quantization errors. A distributed fixed-time controller is proposed to ensure that each follower USV can enter into a convex hull spanned by trajectories of the leader USVs in a user-defined time. Finally, simulation results demonstrate the effectiveness of the proposed control algorithm and the superior of the proposed schemes.

关键词： Containment control Fixed-time stability Sliding mode control (SMC) Minimum learning parameter (MLP) Underactuated surface vessels (USVs) input quantization

来源：评论

学校读者我要写书评

暂无评论

Adaptive Predefined Time Control for Stochastic Switched Nonlinear Systems With Full-State Error Constraints and input quantization

引用

IEEE TRANSACTIONS ON CYBERNETICS 2025年第5期55卷 2261-2272页

作者： Yang, Yu Sui, Shuai Liu, Tengfei Chen, C. L. Philip Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510641 Peoples R China

A neural network adaptive quantized predefined-time control problem is studied for switching stochastic nonlinear systems with full-state error constraints under arbitrary switching. Unlike previous research on rapid convergence, the predefined-time stability criteria are introduced and established for stochastic nonlinear systems, ensuring the stabilization of the control system within a specified time frame. The chattering issue is avoided and it is split into two limited nonlinear functions using a hysteresis quantizer. To address the full-state error constraint problem, a universal barrier Lyapunov function is presented. The common Lyapunov function approach is used to demonstrate the stability of controlled systems. The results demonstrate that the proposed control method ensures all closed-loop signals are probabilistically practically predefined time-stabilized (PPTS), with the system output closely tracking the specified reference signal. Finally, simulated examples validate the effectiveness of the suggested control technique.

关键词： Switches Nonlinear systems Control systems Stochastic processes Adaptive systems Convergence Switching systems Process control Lyapunov methods Stability criteria Full-state error constraint input quantization predefined time control stochastic switched nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Command Filter-Based Predefined-Time Adaptive Fuzzy Control for High-Order Nonlinear Interconnected Systems With input quantization

引用

IEEE TRANSACTIONS ON FUZZY SYSTEMS 2025年第4期33卷 1298-1310页

作者： Zhao, Lin Sui, Shuai Liu, Tengfei Chen, Chun-Lung Philip Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China Northeastern Univ State Key Lab Synthet Automation Proc Ind Shenyang 110004 Peoples R China South China Univ Technol Sch Comp Sci & Engn Guangzhou 510641 Peoples R China

This article focuses on studying an adaptive fuzzy predefined-time tracking control problem for uncertain high-order nonlinear interconnected systems with input quantization. The considered plants contain unknown nonlinear functions, quantized input signals, and external disturbances. Fuzzy logic systems (FLSs) are employed to estimate the unknown nonlinear functions, and by using its structural properties, the difficulty of designing the state variable functions is simplified. By employing adaptive backstepping recursive technique combined with power-based Lyapunov functions, the predefined-time control strategy is presented. Notably, a novel predefined-time filter is used to avoid repeated differentiation of virtual control functions. By applying predefined-time Lyapunov stability theory, the stability analysis demonstrates that all signals in the closed-loop systems remain bounded and the tracking error converges within a predefined settling time. Ultimately, a simulation example is provided to illustrate the validity of the proposed control strategy.

关键词： Interconnected systems quantization (signal) Backstepping Nonlinear systems Control systems Adaptive systems Vectors Lyapunov methods Trajectory Stability criteria Fuzzy logic system high-order interconnected systems input quantization predefined-time control predefined-time filter

来源：评论

学校读者我要写书评

暂无评论

Finite-Time Adaptive Neural Prescribed Performance Control for High-Order Nonlinearly Parameterized Switched Systems With Unmodeled Dynamics and input quantization

引用

IEEE ACCESS 2024年 12卷 4618-4630页

作者： Zhang, Jiao-Jun Zhou, Yong-Hua Sun, Qi-Ming Zhejiang Sci Tech Univ Dept Math Sci Hangzhou 310018 Peoples R China Nanjing Forestry Univ Coll Informat Sci & Technol Nanjing 210037 Peoples R China

This study focuses on the adaptive prescribed-time neural control for a class of high-order switched systems with nonlinear parameterization in presence of unmodeled dynamics and quantized input. Different from the existing results on finite-time control on basis of adding a power integrator technique, the controller construction and stability analysis are simplified, and the tracking error remains within a set range over any prescribed time. Under the frame of backstepping design, a state feedback controller is designed. During the controller design procedure, Radial basis function (RBF) neural networks with minimal learning parameters are employed to identify the unknown compounded nonlinear functions, and the control input is quantized. Based on Lyapunov stability theory, the closed-loop system's signals are all assured to be semi-globally uniformly bounded (SGUB), and the tracking error is kept inside a prescribed zone at a finite time. Finally, a numerical simulation is provided to demonstrate the viability and efficacy of the control strategy.

关键词： High-order nonlinear systems nonlinear parameterization switched systems prescribed-time control unmodeled dynamics input quantization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：