Journal of The Franklin Institute-engineering and Applied Mathematics最新文献

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Dynamic output feedback fuzzy sliding mode learning attitude control for hypersonic flight vehicle with actuator rate constraint 基于作动器速率约束的高超声速飞行器动态输出反馈模糊滑模学习姿态控制

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-25 DOI: 10.1016/j.jfranklin.2025.108374

Xiaoxiang Hu , Yuewen Wang , Jingwen Xu , Jingyan Zhao , Bing. Xiao

By considering the actuator rate constraint and measurable output of hypersonic flight vehicle’s (HFV) attitude system, a dynamic output feedback sliding mode learning controller (DOFSMLC) is proposed in this paper. The proposed DOFSMLC can solve the controller design of nonlinear system with incomplete measurable state, system uncertainties and input rate constraint simultaneously. The nonlinear model of HFV’s attitude system is firstly represented by T-S fuzzy model, then the actuator rate constraint is proposed. Based on the original tracking control objective of HFV’s attitude system, the control objective of the T-S fuzzy model is built. Then a dynamic output feedback (DOF) based sliding surface is design and the stability of the designing sliding surface is guaranteed by selecting appropriate dynamic feedback parameters. A traditional discontinuous reaching law is deigned without considering the actuator rate constraint, and then a sliding mode learning control (SMLC) with iterative updating law is designed. By the designed SMLC, the actuator rate constraint and the system stability requirements can be guaranteed synchronously. Finally, the proposed DOFSMLC is applied on the nonlinear model of HFV’s attitude system, and the simulation results validate the effectiveness of the presented controller

针对高超声速飞行器姿态系统的执行器速率约束和可测输出，提出了一种动态输出反馈滑模学习控制器（DOFSMLC）。该方法可以同时解决具有不完全可测状态、系统不确定性和输入速率约束的非线性系统的控制器设计问题。首先用T-S模糊模型表示HFV姿态系统的非线性模型，然后提出了执行器速率约束。在原HFV姿态系统跟踪控制目标的基础上，建立了T-S模糊模型的控制目标。然后设计了基于动态输出反馈的滑动面，并通过选择合适的动态反馈参数来保证所设计滑动面的稳定性。设计了不考虑执行器速率约束的传统不连续趋近律，设计了具有迭代更新律的滑模学习控制。通过设计的SMLC，可以同步保证执行器的速率约束和系统的稳定性要求。最后，将所提出的DOFSMLC应用于HFV姿态系统的非线性模型，仿真结果验证了所提控制器的有效性

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引用次数: 0

Stabilization of reaction-diffusion PDE with spatially-varying distributed input delay 具有空间变化分布输入延迟的反应扩散微分方程的镇定

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-24 DOI: 10.1016/j.jfranklin.2025.108375

Xiaodan Feng, Dandan Guo

This paper discusses the stabilization of reaction-diffusion PDE with spatially-varying distributed delay affecting in-domain control. The innovation of this paper is that the distributed delay in integral form, which can include any constant/spatially-varying delay in non-integral form, is more general. The unstable parts of the infinite dimensional reaction-diffusion system are converted into a finite dimensional truncated model, and the spatially-varying delay is divided into a nominal constant delay and a residual term. For the finite dimensional truncated model with the residual term, we introduce a novel backstepping transformation to obtain projection coefficients of control onto a set of basis, resulting in a constant-delay predictor feedback control. We demonstrate that the closed-loop system is exponentially stable as long as the spatially-varying delay has a sufficiently small variation near its nominal constant value. Numerical simulations illustrate the effectiveness of the proposed constant-delay predictor feedback control.

讨论了影响域内控制的具有空间变化分布延迟的反应扩散微分方程的镇定问题。本文的创新之处在于，积分形式的分布延迟可以包含任意非积分形式的常数/空间变化延迟，具有更广泛的通用性。将无限维反应扩散系统的不稳定部分转化为有限维截断模型，并将空间变化延迟分为标称常数延迟和残差项。对于带有残差项的有限维截断模型，我们引入了一种新的反演变换来获得控制在一组基上的投影系数，从而得到一种常延迟预测器反馈控制。我们证明了只要空间变化时滞在其标称常数值附近有足够小的变化，闭环系统是指数稳定的。数值仿真验证了所提出的恒延时预测器反馈控制的有效性。

引用次数: 0

An advanced data-driven method for nonlinear no-Gaussian quality-oriented fault diagnosis 一种基于数据驱动的非线性非高斯质量故障诊断方法

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-23 DOI: 10.1016/j.jfranklin.2025.108348

Chengyuan Sun , Xuesong Wang , Yuhu Cheng

This paper studies the problem of high false alarm rates in the nonlinear no-Gaussian quality-oriented fault diagnosis framework. Compared with existing methods, advanced data-driven (ADD) leverages information entropy to handle nonlinear non-Gaussian data, thereby enhancing the accuracy and robustness of fault detection while avoiding the assumption of Gaussian distributions. The preprocessing-postprocessing strategy and quality-oriented fault detection high-order indices are designed to ensure the correct correlation between faults and quality indicators. In addition, the pseudo-samples fault location method mitigates the smear effect in kernel function to identify faulty reasons. In the end, the effectiveness of ADD is verified through experimental results obtained from both simulation and industrial scenarios.

研究了非线性非高斯质量导向故障诊断框架中虚警率高的问题。与现有方法相比，先进数据驱动（advanced data-driven， ADD）方法利用信息熵来处理非线性非高斯数据，从而提高了故障检测的准确性和鲁棒性，同时避免了高斯分布的假设。设计了前后处理策略和面向质量的故障检测高阶指标，保证了故障与质量指标之间的正确关联。此外，伪样本故障定位方法减轻了核函数中的涂抹效应，可以有效地识别故障原因。最后，通过仿真和工业场景的实验结果验证了ADD的有效性。

引用次数: 0

Controllability and observability of fractional higher-order neural networks via distributed delays 基于分布延迟的分数阶高阶神经网络的可控性和可观察性

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-23 DOI: 10.1016/j.jfranklin.2025.108362

Chenjun Ma , Weiyuan Ma , Yueheng Wang

This article investigates the controllability and observability of fractional higher-order neural networks subject to distributed delays in the control function. The necessary and sufficient criteria for controllability and observability of linear fractional systems are established through the construction of dedicated Gramian matrices. To handle the nonlinear, higher-order network setting, Schauder’s fixed point theorem and Banach’s contraction mapping principle are employed to derive sufficient conditions for controllability and observability, respectively. The theoretical framework is illustrated and validated through three example scenarios, highlighting the effectiveness and broad applicability of the proposed approach. These findings provide an extensive foundation for advanced control and observation design in complex neural networks with fractional dynamics, higher-order interactions, and practical delay effects.

研究了控制函数具有分布时滞的分数阶高阶神经网络的可控性和可观察性。通过构造专用的Gramian矩阵，建立了线性分数阶系统的可控性和可观测性的充分必要判据。针对非线性高阶网络设置，利用Schauder不动点定理和Banach收缩映射原理分别导出了网络的可控性和可观测性的充分条件。理论框架通过三个示例场景进行说明和验证，突出了所提出方法的有效性和广泛适用性。这些发现为具有分数阶动力学、高阶相互作用和实际延迟效应的复杂神经网络的高级控制和观察设计提供了广泛的基础。

引用次数: 0

Collision-free trajectory planning for unmanned vehicles using sequential second-order cone programming 基于序贯二阶锥规划的无人驾驶车辆无碰撞轨迹规划

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-22 DOI: 10.1016/j.jfranklin.2025.108283

Xiaoming Liu , Fuchun Wu , Yunshan Deng , Ming Wang , Yuanqing Xia

This paper addresses the trajectory planning problem for unmanned vehicles with free terminal time in constrained environments with obstacles. A variable substitution method is employed to handle the free terminal time, transforming the nonconvex cost function and constraints into convex forms while maintaining feasibility. For obstacle avoidance, we propose a Chebyshev-node based discretization method that focuses on the vertices of vehicles and obstacles modeled as convex polygons, along with a convexification approach for volumetric obstacle avoidance. The optimization problem is solved within a sequential convex programming framework by converting it into a series of second-order cone programming subproblems, enhancing real-time performance. The effectiveness and computational efficiency of the proposed method are validated through numerical simulations and comparisons with other methods.

研究了具有自由终端时间的无人驾驶车辆在有障碍物约束环境中的轨迹规划问题。采用变量代换法处理自由终端时间，在保持可行性的前提下，将非凸代价函数和约束转化为凸形式。对于避障，我们提出了一种基于chebyshev节点的离散化方法，该方法将车辆和障碍物的顶点建模为凸多边形，以及一种凸化方法用于体积避障。通过将优化问题转化为一系列二阶锥规划子问题，在序列凸规划框架内求解优化问题，提高了实时性。通过数值模拟和与其他方法的比较，验证了该方法的有效性和计算效率。

引用次数: 0

Estimation of maximum allowable sampling interval for hybrid systems with aperiodic sampling using the event-triggered approach 用事件触发法估计非周期采样混合系统的最大允许采样间隔

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-21 DOI: 10.1016/j.jfranklin.2025.108334

Yan He , Lushuang Gao , Xiaoyu Yang , Ruijun Liu , Xuncai Zhang

The paper investigates the estimation problem for a class of nonlinear hybrid systems with aperiodic sampling. First, an aperiodic sampling mechanism is proposed using the event-triggered approach, in which a aperiodic sampling hybrid model is developed to describe the nonlinear systems. Second, the exponential stability is analyzed for the considered nonlinear hybrid model based on the Lyapunov function methods, and the stability rate is studied under different Lyapunov functions. In particular, a sufficient condition is provided to analyze the linear hybrid model. Third, an improved estimation method is proposed to derive the maximum allowable sampling interval (MASI) by constructing a new ordinary differential equation. Finally, several practical models are illustrated to verify the effectiveness of the proposed theorems.

研究了一类具有非周期采样的非线性混合系统的估计问题。首先，提出了一种采用事件触发方法的非周期采样机制，其中建立了非周期采样混合模型来描述非线性系统。其次，分析了基于Lyapunov函数方法的考虑的非线性混合模型的指数稳定性，并研究了不同Lyapunov函数下的稳定率。特别地，给出了分析线性混合模型的充分条件。第三，提出了一种改进的估计方法，通过构造新的常微分方程推导出最大允许抽样区间（MASI）。最后，通过几个实际模型验证了所提定理的有效性。

引用次数: 0

Event-triggered based finite-time adaptive control for multi-agent systems with unknown input delay and input quantization 具有未知输入延迟和输入量化的多智能体系统的事件触发有限时间自适应控制

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-21 DOI: 10.1016/j.jfranklin.2025.108351

Xiaonan Xia, Zihang Tong, Tianping Zhang, Jianwen Pan

A finite-time state event-triggered control strategy is developed based on adaptive dynamic surface control (DSC) approach for multi-agent nonlinear systems including unknown time-varying input delays and input quantization. The designed dynamic state-based event triggering mechanism is set to trigger the control signal when the system state error exceeds the dynamic threshold, and error calculation relies on partial neighbor agent information and local measurement information. A new input filtering error compensation system suitable for systems with input delay is designed. The semi-global finite-time stability of closed-loop systems with input delay is proven by constructing Lyapunov functionals, ensuring consensus error convergence and avoiding Zeno phenomenon. Finally, simulation results are presented to confirm the efficacy of the proposed control strategy.

针对包含未知时变输入时滞和输入量化的多智能体非线性系统，提出了一种基于自适应动态面控制（DSC）的有限时间状态事件触发控制策略。设计了基于动态状态的事件触发机制，当系统状态误差超过动态阈值时触发控制信号，误差计算依赖于部分邻居代理信息和局部测量信息。设计了一种适用于有输入延迟系统的输入滤波误差补偿系统。通过构造Lyapunov泛函，证明了具有输入时滞的闭环系统的半全局有限时间稳定性，保证了一致误差收敛，避免了Zeno现象。最后通过仿真结果验证了所提控制策略的有效性。

引用次数: 0

A disturbance observer-based synchronization control architecture for Euler-Lagrange networks with a dynamic leader 基于扰动观测器的动态前导欧拉-拉格朗日网络同步控制体系

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-21 DOI: 10.1016/j.jfranklin.2025.108360

Mohammad Motaharifar, Mohammad Ataei

This paper explores the challenges of synchronizing Euler-Lagrange networks that include a dynamic leader, utilizing a disturbance observer method. In this network, each agent is characterized by Euler-Lagrange equations of motion with dynamics that are not fully known. Unlike most existing approaches for handling uncertainties in Euler-Lagrange networks, the structure of the dynamic equations is assumed to be unavailable, making existing adaptive control schemes inapplicable. Therefore, a new formulation is proposed for Euler-Lagrange networks to lump the uncertain dynamical terms, estimate them, and suppress their effects accordingly. The closed-loop stability of the overall system is analyzed using the Lyapunov stability theorem. Simulation results show that the proposed approach outperforms two existing benchmark control methods.

本文探讨了同步欧拉-拉格朗日网络的挑战，包括一个动态的领导者，利用扰动观测器的方法。在这个网络中，每个智能体都用欧拉-拉格朗日运动方程来表征，其动力学是不完全已知的。与大多数现有的处理欧拉-拉格朗日网络不确定性的方法不同，动态方程的结构被假设为不可用，使得现有的自适应控制方案不适用。因此，本文提出了一种新的欧拉-拉格朗日网络的混合、估计和抑制不确定动态项的公式。利用李雅普诺夫稳定性定理分析了整个系统的闭环稳定性。仿真结果表明，该方法优于现有的两种基准控制方法。

引用次数: 0

Chattering-free adaptive sliding mode control for uncertain delayed stochastic systems with impulsive dynamics 不确定时滞脉冲系统的无抖振自适应滑模控制

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-21 DOI: 10.1016/j.jfranklin.2025.108323

Xiaonan Liu , Wenrui Li , Jian Sun , Yonggui Kao

This paper develops a chattering-free sliding mode control framework for uncertain stochastic systems subject to hybrid dynamics, including time-varying delays and impulsive perturbations. A novel integral sliding surface is designed to incorporate time-varying delays, parametric uncertainties, and impulsive perturbations, thereby unifying the analysis of continuous and discrete dynamics. Furthermore, the proposed adaptive scheme with the hyperbolic tangent function ensures chattering suppression while maintaining finite-time convergence from the initial moment. Additionally, sufficient conditions for the stability of the stochastic system are derived on the specified sliding surface for all admissible uncertainties, based on the Lyapunov function and the average impulsive interval. Finally, a numerical example is presented to illustrate the proposed method.

针对含时变时滞和脉冲扰动的混合动力学不确定随机系统，提出了一种无抖振滑模控制框架。设计了一种包含时变时滞、参数不确定性和脉冲摄动的新型积分滑动面，从而统一了连续和离散动力学的分析。此外，提出的双曲正切函数自适应方案在抑制抖振的同时保持自初始时刻起的有限时间收敛性。此外，基于Lyapunov函数和平均脉冲区间，导出了在给定滑动面上所有允许不确定性的随机系统稳定的充分条件。最后，给出了一个数值算例来说明所提出的方法。

引用次数: 0

Two-stage auxiliary model maximum likelihood least squares-based iterative estimation method for general stochastic multivariable systems 一般随机多变量系统的两阶段辅助模型极大似然最小二乘迭代估计方法

IF 4.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

Journal of The Franklin Institute-engineering and Applied Mathematics

Pub Date : 2025-12-20 DOI: 10.1016/j.jfranklin.2025.108349

Qian Zhang, Ximei Liu

This paper investigates computationally efficient identification methods for multivariable autoregressive output-error autoregressive moving-average systems. To tackle high-dimensional parameter estimation challenges, the multivariable system is decomposed into several subsystems. Furthermore, each subsystem identification model is decomposed into two small-scale sub-identification models to reduce the computational burden. Based on the hierarchical identification principle, a two-stage auxiliary model maximum likelihood least squares-based iterative algorithm is proposed. The analysis of floating point operations shows that the proposed algorithm achieves higher computational efficiency than the existing auxiliary model maximum likelihood least squares-based iterative algorithm. Simulation results demonstrate that the proposed algorithm is effective and achieves high parameter estimation accuracy.

研究了多变量自回归输出误差自回归移动平均系统的高效辨识方法。为了解决高维参数估计问题，将多变量系统分解为多个子系统。此外，为了减少计算量，将每个子系统识别模型分解为两个小尺度子识别模型。基于分层识别原理，提出了一种基于两阶段辅助模型极大似然最小二乘的迭代算法。浮点运算分析表明，该算法比现有的基于辅助模型的极大似然最小二乘迭代算法具有更高的计算效率。仿真结果表明，该算法是有效的，具有较高的参数估计精度。

引用次数: 0

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