ISA transactions最新文献_第6页

Robust backstepping control of side-by-side unmanned helicopter based on fuzzy neural networks extended state observer 基于模糊神经网络扩展状态观测器的并排无人直升机鲁棒反演控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.003

Suiyuan Shen, Mingle Zhang, Mengyao Li, Jiyu Li

The combined influence of mass-inertia variations and aerodynamic disturbances generates coupled uncertainties that substantially degrade the positioning and attitude stability of side-by-side unmanned helicopters. To mitigate these issues, this study develops a control strategy integrating a fuzzy neural network-enhanced extended state observer with robust backstepping control (FNNESO-RBSC). The core innovation lies in utilizing the FNN to accurately estimate the time-varying total disturbance within the ESO framework, overcoming the limitation of conventional fixed-gain ESO. This advanced observation mechanism enables dynamic disturbance compensation within the backstepping control law. The flight control system is subsequently developed and validated through hardware-in-loop (HIL) simulations. Experimental results demonstrate that the proposed controller achieves superior performance compared with conventional active disturbance rejection control (ADRC) and adaptive neural network ESO-based finite-time convergent sliding mode control (ANNESO-FTCSMC) methods, exhibiting enhanced disturbance rejection, improved robustness, and higher trajectory tracking accuracy across varying operational scenarios.

质量惯性变化和气动扰动的综合影响产生了耦合不确定性，极大地降低了并排无人直升机的定位和姿态稳定性。为了缓解这些问题，本研究开发了一种将模糊神经网络增强的扩展状态观测器与鲁棒反演控制（FNNESO-RBSC）相结合的控制策略。其核心创新在于利用FNN在ESO框架内准确估计时变总扰动，克服了传统固定增益ESO的局限性。这种先进的观察机制使反演控制律内的动态扰动补偿成为可能。飞行控制系统随后通过硬件在环（HIL）仿真进行了开发和验证。实验结果表明，与传统的自抗扰控制（ADRC）和基于自适应神经网络eso的有限时间收敛滑模控制（ANNESO-FTCSMC）方法相比，该控制器具有更强的抗扰性，增强了鲁棒性，并在不同的操作场景下具有更高的轨迹跟踪精度。

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引用次数: 0

Implicit Euler discretization for chattering suppression in non-singular terminal sliding mode control 非奇异末端滑模控制中颤振抑制的隐式欧拉离散化。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.022

Shanhai Jin, Yuhan Wang, Dejin Zhao, Xiaodan Wang, Changfu Jin

Numerical chattering limits digital implementation of non-singular terminal sliding mode control (NTSMC) despite its theoretical advantages. This paper presents an implicit Euler discretization for NTSMC that suppresses numerical chattering while preserving finite-time convergence through polynomial reformulation with signum-projection equivalence for explicit control computation. Discrete Lyapunov analysis establishes finite-time convergence and first-order accuracy, while strong numerical damping allows larger sampling periods than explicit methods. Comparative simulations with five discretization methods and hardware experiments on STM32-based PMSM control achieved 24-fold steady-state error reduction compared to explicit discretization and

{0.083}^{\circ}

accuracy with 6.35

μ

s computation time at 2 kHz control.

数值抖振限制了非奇异终端滑模控制（NTSMC）的数字化实现，尽管它在理论上具有优势。本文提出了NTSMC的隐式欧拉离散化方法，该方法通过对显式控制计算采用符号-投影等价的多项式重新表述来抑制数值抖振，同时保持有限时间收敛。离散李雅普诺夫分析建立有限时间收敛和一阶精度，而强数值阻尼允许比显式方法更大的采样周期。5种离散化方法的对比仿真和基于stm32的PMSM控制的硬件实验，在2 kHz控制下以6.35 μs的计算时间实现了比显式离散化减少24倍的稳态误差和0.083°精度。

引用次数: 0

Weighted minimum variance based on-line performance assessment of multivariate processes: A data-driven approach 基于加权最小方差的多变量过程在线性能评估：一种数据驱动方法。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.015

Xu-Teng Shi, Chun-Qing Huang

In multivariate processes, the previous minimum variance benchmarking techniques still lack an on-line applicability for industrial implementation under routine operating conditions due to the fact that the minimum required process knowledge cannot be obtained from the routine operating data. A data-driven approach is proposed for the on-line performance assessment without relying on prior process knowledge, where the weighted minimum variance benchmark is directly estimated from the closed-loop output data under routine operating conditions. Moreover, in the case of that the knowledge of the multivariate process is available, the practical scheme is proposed for on-line benchmark estimation by using the routine operating data, in which the prior process knowledge is employed by means of the proposed normalizability of first non-zero impulse response coefficient of the plant. In the case study of “Shell” heavy oil fractionator, the effectiveness of the proposed approach is verified from the benchmark/index on-line estimations, their relative estimation errors and time cost for each update.

在多变量过程中，由于不能从常规操作数据中获得所需的最小过程知识，先前的最小方差基准测试技术仍然缺乏在常规操作条件下工业实施的在线适用性。提出了一种数据驱动的在线性能评估方法，该方法不依赖于先验过程知识，直接从常规运行条件下的闭环输出数据估计加权最小方差基准。此外，在多元过程知识可用的情况下，提出了一种利用常规运行数据进行在线基准估计的实用方案，该方案通过提出的装置第一非零脉冲响应系数的归一化性来利用先验过程知识。以“壳牌”稠油分馏器为例，从基准/指标在线估计、相对估计误差和每次更新的时间成本等方面验证了所提方法的有效性。

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引用次数: 0

Lyapunov-based zone economic MPC for safe and efficient drilling under variable measurement delays 基于lyapunov的区域经济MPC，可在可变测量延迟下实现安全高效的钻井。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.026

Yilong Zhang , Baochang Xu , Zhuoran Meng , Pengxiang You , Ruijie Gao , Jun Yao

During drilling, downhole measurements are often affected by time-varying measurement delays and intermittent data loss. The driller cannot adjust manipulated variables such as surface Weight on Bit (WOB_s), surface Revolutions per Minute (RPM_s), and mud pump flow rate continuously. This prevents the drilling system from operating at its optimum state in real-time, ultimately diminishing both safety and efficiency. To address these challenges, we develop an integrated coupled model of the drilling process, characterizing the relationship between Rate of Penetration (ROP) and Bottom Hole Pressure (BHP). Based on this model, we propose a novel Model Predictive Control (MPC) algorithm, the Lyapunov-based Zone Economic Model Predictive Control (LZEMPC) algorithm. This algorithm can manage BHP and optimize ROP concurrently, even under time-varying measurement delays and data loss. We use field data to conduct simulation experiments. The results demonstrate that the LZEMPC algorithm successfully maintains BHP within the formation pressure window while significantly improving drilling efficiency. In comparison to traditional methods, the LZEMPC approach effectively manages both safety and efficiency, providing a promising solution for real-time drilling optimization in challenging environments.

在钻井过程中，井下测量经常受到时变测量延迟和间歇性数据丢失的影响。司钻不能连续调整被操纵的变量，如地面钻压（WOBs）、地面每分钟转数（rpm）和泥浆泵流量。这使得钻井系统无法实时运行在最佳状态，最终降低了安全性和效率。为了应对这些挑战，我们开发了一个钻井过程的集成耦合模型，描述了钻速（ROP）和井底压力（BHP）之间的关系。在此基础上，提出了一种新的模型预测控制算法——基于lyapunov的区域经济模型预测控制算法（LZEMPC）。该算法可以同时管理BHP和优化ROP，即使在时变测量延迟和数据丢失的情况下也是如此。我们利用现场数据进行模拟实验。结果表明，LZEMPC算法成功地将BHP保持在地层压力窗口内，同时显著提高了钻井效率。与传统方法相比，LZEMPC方法有效地管理了安全性和效率，为在具有挑战性的环境中进行实时钻井优化提供了一种有前景的解决方案。

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引用次数: 0

Rule-based safety optimization and dynamical anti-disturbance control: Application to point-to-point transitions for multiple autonomous surface vehicles with semi-physical experiments 基于规则的安全优化与动态抗干扰控制：基于半物理实验的多自主地面车辆点对点过渡的应用

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-01-01 DOI: 10.1016/j.isatra.2025.11.042

Yanping Xu , Nan Gu , Tieshan Li , Weidong Zhang , Zhouhua Peng

This paper addresses the safety-certified point-to-point transition problem of multiple underactuated autonomous surface vehicles (ASVs) operating in a congested maritime environment. The main idea of this paper is to develop a novel rule-based safety optimization approach, combined with a dynamic anti-disturbance control strategy, to enable collision-free point-to-point transitions. The key features are twofold: ensuring the safe navigation of ASVs while minimizing the impact on the point-to-point transition task; and realizing precise kinetic control without relying on any prior knowledge of ASV model parameters. Specifically, at the kinematic level, nominal guidance laws are designed for position stabilization. Three rule-based control barrier functions are formulated to impose safety constraints on resultant velocity and yaw rate. The optimal guidance signals are obtained by solving a quadratic programming problem. At the kinetic level, extended state observers are designed to estimate the extended state, which unifies nonlinear dynamics, external disturbances, and control inputs. The estimates are then used to design dynamic controllers for velocity and yaw rate tracking. It is proven that the closed-loop control system is input-to-state stable, and that the safety of the multi-ASV system is also ensured. Both comparative results and semi-physical experimental results are elaborated to substantiate the efficacy of the proposed rule-based safety optimization and dynamical anti-disturbance control method.

本文研究了在拥挤的海上环境中运行的多个欠驱动自动水面车辆（asv）的安全认证点对点转换问题。本文的主要思想是开发一种新的基于规则的安全优化方法，结合动态抗干扰控制策略，以实现无碰撞的点到点转换。主要特点有两个：确保自动驾驶汽车的安全导航，同时最大限度地减少对点到点转换任务的影响；在不依赖任何ASV模型参数先验知识的情况下实现精确的动力学控制。具体地说，在运动水平上，标称制导律被设计用于位置稳定。提出了三个基于规则的控制障碍函数，对合成速度和横摆角速度施加安全约束。通过求解二次规划问题得到最优制导信号。在动力学水平上，设计了扩展状态观测器来估计扩展状态，将非线性动力学、外部干扰和控制输入统一起来。然后将估计值用于设计速度和偏航率跟踪的动态控制器。验证了闭环控制系统的输入到状态稳定，保证了多asv系统的安全性。对比结果和半物理实验结果验证了所提出的基于规则的安全优化和动态抗干扰控制方法的有效性。

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引用次数: 0

An adaptive feature extraction technique via bispectrum-driving graph domain for bearing fault diagnosis 基于双谱驱动图域的自适应特征提取技术用于轴承故障诊断。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2025-12-01 DOI: 10.1016/j.isatra.2025.09.020

Miaorui Yang , Kun Zhang , Haihong Tang , Yonggang Xu , Wenyu Huo

The rapid development of the mechanical industry has made fault feature extraction based on vibration signals increasingly challenging. The emergence of graph signal processing theory offers a new perspective for signal feature extraction. This study aims to provide an adaptive feature extraction technique via bispectrum-driven graph domain for bearing fault diagnosis. Initially, the bispectrum is established as the core of graph signal construction to pre-demodulate the modulation components in the signal, thereby enhancing the accuracy and interpretability of graph signal processing. Subsequently, an optimal node identification technique is developed to find effective components in the graph signal eigenvalues. Finally, the use of optimal eigenvalues to extract feature information from graph signals is demonstrated through rigorous mathematical derivation, achieving accurate and reliable fault diagnosis. The experimental work presented here illustrates the practical effectiveness of the method for bearing fault signals.

随着机械工业的快速发展，基于振动信号的故障特征提取越来越具有挑战性。图信号处理理论的出现为信号特征提取提供了一个新的视角。本研究旨在为轴承故障诊断提供一种基于双谱驱动图域的自适应特征提取技术。首先建立双谱作为图信号构建的核心，对信号中的调制成分进行预解调，从而提高图信号处理的准确性和可解释性。随后，提出了一种最优节点识别技术，在图信号特征值中寻找有效分量。最后，通过严格的数学推导，证明了利用最优特征值从图信号中提取特征信息，实现了准确可靠的故障诊断。本文的实验工作说明了该方法对轴承故障信号的实际有效性。

引用次数: 0

Optimized voltage vector selection for dual-star induction motor: Robust predictive direct torque control-based hysteresis-free approach 双星感应电机电压矢量优化选择：基于鲁棒预测直接转矩控制的无迟滞方法。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2025-12-01 DOI: 10.1016/j.isatra.2025.09.015

Amel Kasri , Kamel Ouari , Youcef Belkhier , Djamel Ziane , Mohamed Fouad Benkhoris , Mohamed Benbouzid

The dual-star induction machine is a widely adopted multiphase machine in industrial applications, thanks to its superior reliability in managing power supply faults and enhanced robustness. This study presents a robust predictive DTC strategy for a dual-star induction motor supplied by dual-voltage source inverters. Relying on a cost function optimization, the suggested predictive DTC algorithm replaces traditional hysteresis regulators and switching tables typically employed in classical DTC, determining the optimal sequence of voltage space vectors. Regarding speed regulation, the proposed MPC framework incorporates integral action, eliminating steady-state inaccuracies and improving disturbance rejection under model uncertainties and external perturbations. Real-time validation on the OPAL-RT platform confirms the effectiveness of the proposed scheme. Compared with conventional DTC, torque and flux ripples are reduced by 83.95 % and 74.75 %, respectively, while current THD decreases by 77.89 %. In addition, the speed response time improves by 82.5 %, and the rejection time by 97 %. These results highlight the robustness and efficiency of the proposed RPDTC technique, making it a strong candidate for high-performance DSIM drive applications.

双星感应电机在电源故障管理方面具有优越的可靠性和增强的鲁棒性，是工业应用中广泛采用的多相电机。针对双电压源逆变器供电的双星感应电机，提出了一种鲁棒预测直接转矩控制策略。基于成本函数优化，本文提出的预测式DTC算法取代了传统的迟滞调节器和开关表，确定了电压空间矢量的最优序列。在速度调节方面，所提出的MPC框架结合了积分作用，消除了稳态误差，提高了模型不确定性和外部扰动下的抗扰性。OPAL-RT平台上的实时验证验证了该方案的有效性。与传统直接转矩控制相比，转矩和磁链脉动分别减小了83.95%和74.75%，电流THD减小了77.89%。速度响应时间提高了82.5%，抑制时间提高了97%。这些结果突出了所提出的RPDTC技术的鲁棒性和效率，使其成为高性能DSIM驱动器应用的有力候选。

{"title":"Optimized voltage vector selection for dual-star induction motor: Robust predictive direct torque control-based hysteresis-free approach","authors":"Amel Kasri , Kamel Ouari , Youcef Belkhier , Djamel Ziane , Mohamed Fouad Benkhoris , Mohamed Benbouzid","doi":"10.1016/j.isatra.2025.09.015","DOIUrl":"10.1016/j.isatra.2025.09.015","url":null,"abstract":"<div><div>The dual-star induction machine is a widely adopted multiphase machine in industrial applications, thanks to its superior reliability in managing power supply faults and enhanced robustness. This study presents a robust predictive DTC strategy for a dual-star induction motor supplied by dual-voltage source inverters. Relying on a cost function optimization, the suggested predictive DTC algorithm replaces traditional hysteresis regulators and switching tables typically employed in classical DTC, determining the optimal sequence of voltage space vectors. Regarding speed regulation, the proposed MPC framework incorporates integral action, eliminating steady-state inaccuracies and improving disturbance rejection under model uncertainties and external perturbations. Real-time validation on the OPAL-RT platform confirms the effectiveness of the proposed scheme. Compared with conventional DTC, torque and flux ripples are reduced by 83.95 % and 74.75 %, respectively, while current THD decreases by 77.89 %. In addition, the speed response time improves by 82.5 %, and the rejection time by 97 %. These results highlight the robustness and efficiency of the proposed RPDTC technique, making it a strong candidate for high-performance DSIM drive applications.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"167 ","pages":"Pages 2078-2093"},"PeriodicalIF":6.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven modeling and adaptive event-triggered secure control for autonomous vehicles subject to sensor attacks 受传感器攻击的自动驾驶汽车的数据驱动建模和自适应事件触发安全控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2025-12-01 DOI: 10.1016/j.isatra.2025.09.036

Hong-Tao Sun , Xinyu Xie , Miao Rong , Zongying Feng , Chen Peng

This paper is concerned with data-driven model identification and adaptive event-triggered secure control of autonomous vehicles subject to sensor attacks. Firstly, the lateral dynamical model of autonomous vehicles is identified from data by exploiting the dynamic mode decomposition (DMD) approach and the sensor attacks are considered based on the established model. Then, an adaptive event-triggered scheme is well developed to balance the communication efficiency and control performance. Thus, the sliding-mode-like control scheme is utilized to counteract the sensor attacks. The stability analysis and stabilization design are derived using Lyapunov theory and linear matrix inequalities technique. There are three advantages of the proposed control scheme: a) DMD overcomes modeling difficulties, b) event-triggered threshold is adaptively regulated by the feedback measurement and c) the sensor attacks can be actively mitigated. At last, several comparison examples show the effectiveness of the proposed data-driven secure control scheme.

研究了受传感器攻击的自动驾驶汽车的数据驱动模型识别和自适应事件触发安全控制问题。首先，利用动态模态分解（DMD）方法从数据中识别自动驾驶汽车的横向动力学模型，并在此基础上考虑传感器攻击；然后，开发了一种自适应事件触发方案，以平衡通信效率和控制性能。因此，采用类滑模控制方案来对抗传感器攻击。利用李雅普诺夫理论和线性矩阵不等式技术推导了系统的稳定性分析和稳定性设计。所提出的控制方案有三个优点：a) DMD克服了建模困难；b)事件触发阈值由反馈测量自适应调节；c)传感器攻击可以主动减轻。最后，通过实例对比验证了所提数据驱动安全控制方案的有效性。

引用次数: 0

Virtual inertia regulation based high-order observer for weak microgrids using deep sequential learning 基于深度顺序学习的弱微电网虚拟惯性调节高阶观测器。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2025-12-01 DOI: 10.1016/j.isatra.2025.10.005

Shuguang Li , Shupeng Song , Mai The Vu

The high penetration of sustainable energy resources (SERs) into the hybrid Micro-grid system (HMGS) is equipped with AC/DC/DC power converters to connect such generation units to the bus. Since these power electronic interfaces do not have rotational mass, the HMGS’s inertia will be reduced accordingly. This study introduces the concept of a virtual frequency controller (VFC) in the energy storage systems (ESSs) employed in a low-inertia HMGS under high penetration of SERs. This paper introduces a new approach to adaptive VFC for low-inertia HMGSs which includes three major innovations: (1) implementation of a high-order extended disturbance observer (HOEDO) for real-time estimation and compensation of unknown dynamics and SER-induced disturbances; (2) applying the deep learning deep sequential action-value learning (SAVL) algorithm to adjust the parameters of the controller-observer in an unsupervised fashion to adapt to system variability and uncertainties without a priori models; and (3) the inclusion of virtual rotor dynamics emulation during primary and secondary control loops to enhance responsiveness akin to synchronous generators. By maximizing a cumulative reward function, the agents of deep SAVL are trained in such a way that the controller is adaptively designed according to SERs/load variations. By deploying the training capability of deep neural networks, the suggested adaptive VFC technique improves the system’s inertia and damping features under high-penetration of SERs. Moreover, comparative responses of the suggested adaptive VFC controller with conventional virtual inertia control (CVIC) controlled by model predictive control (MPC), fractional-order proportional-integral-derivative (FOPID) control, the conventional virtual inertia and virtual damping control-based PI controller, and CVIC-based two-layer multiple MPC (TLMMPC) methods infer that the suggested scheme not only exhibits more suppressed fluctuations but also demonstrates a faster response to the dynamic variations.

可持续能源（SERs）高度渗透到混合微电网系统（HMGS）中，配备AC/DC/DC电源转换器将这些发电机组连接到母线。由于这些电力电子接口没有旋转质量，HMGS的惯性将相应减少。本文介绍了高穿透SERs下低惯性HMGS储能系统中虚拟频率控制器（VFC）的概念。本文介绍了一种低惯性HMGSs自适应VFC的新方法，其中包括三个主要创新：(1)实现高阶扩展扰动观测器（HOEDO），用于实时估计和补偿未知动力学和ser诱导的扰动；(2)应用深度学习深度序列动作值学习（SAVL）算法以无监督的方式调整控制器观测器的参数，以适应系统的可变性和不确定性，而不需要先验模型；(3)在一次和二次控制回路中包含虚拟转子动力学仿真，以提高类似于同步发电机的响应性。通过最大化累积奖励函数，深度SAVL的智能体以这样一种方式进行训练，即控制器根据SERs/负载变化自适应设计。通过部署深度神经网络的训练能力，本文提出的自适应VFC技术改善了系统在高穿透性SERs下的惯性和阻尼特性。此外，本文提出的自适应VFC控制器与模型预测控制（MPC）控制的传统虚拟惯性控制（CVIC）、分数阶比例-积分-导数（FOPID）控制、基于传统虚拟惯性和虚拟阻尼控制的PI控制器的响应进行了比较。和基于cvic的两层多重MPC （TLMMPC）方法推断，该方案不仅具有更好的抑制波动能力，而且对动态变化的响应速度更快。

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引用次数: 0

Global asymptotic practical stability of perturbation-based extremum-seeking control for complex nonlinear systems via small-gain approach 基于微扰的复杂非线性系统小增益寻极值控制的全局渐近实用稳定性。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2025-12-01 DOI: 10.1016/j.isatra.2025.10.012

Jingwei Xu , Zhenghong Jin , Junlong Fang

This paper investigates the extremum-seeking control problem for complex nonlinear systems, aiming to regulate the system output toward a fixed value that maximizes an unknown nonlinear mapping under relaxed conditions. To address this challenge, a novel hierarchical framework is introduced, which decomposes the closed-loop system and reformulates the problem as a stability analysis of an interconnected system. Distinct from conventional methods that rely on exponential stability of the boundary-layer system, the proposed framework ensures robust stability against bounded disturbances by exploiting interconnected gain relations among hierarchical subsystems, while the nonlinear small-gain theorem is employed to ensure the overall stability and feasibility of the proposed approach. Compared to existing literatures, the proposed design allows the global extremum-seeking problem in uncertain nonlinear systems to be solved under more relaxed conditions. Finally, numerical simulations on various nonlinear systems demonstrate the effectiveness and practical applicability of the theoretical results.

本文研究了复杂非线性系统的极值寻求控制问题，目的是在宽松条件下将系统输出调节到一个使未知非线性映射最大的固定值。为了解决这一挑战，引入了一种新的分层框架，该框架将闭环系统分解并将问题重新表述为互联系统的稳定性分析。与依赖于边界层系统指数稳定性的传统方法不同，该框架通过利用分层子系统之间的相互增益关系来确保对有界扰动的鲁棒稳定性，同时采用非线性小增益定理来确保所提方法的整体稳定性和可行性。与现有文献相比，该设计使得不确定非线性系统的全局极值求值问题可以在更宽松的条件下求解。最后，对各种非线性系统进行了数值模拟，验证了理论结果的有效性和实际适用性。

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引用次数: 0