Control Engineering Practice最新文献_第3页

A multi-condition fuzzy clustering method based on rectangular information granules and its application to an industry process 基于矩形信息颗粒的多条件模糊聚类方法及其在工业过程中的应用

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-05-01 Epub Date: 2026-02-09 DOI: 10.1016/j.conengprac.2026.106822

Jie Hu , Fan Yang , Hongxiang Li , Zixin Huang , Witold Pedrycz

Iron ore sintering is governed by highly nonlinear dynamics and multiple operating conditions. The data of the process exhibits characteristics such as noise and imbalance. Traditional clustering methods, such as fuzzy C-means (FCM), often struggle to handle issues such as noise, data imbalance, and fuzzy clustering boundaries. This paper presents a multi-stage clustering framework that unifies information-granule modeling, intelligent optimization, and fuzzy clustering. Unlike conventional point-based methods, rectangular information granules are explicitly constructed to capture boundary uncertainty and subsequently optimized by particle swarm optimization, providing interpretable and adaptive data abstractions. A new weighted fuzzy-granule distance is then introduced to cluster the optimized granules, enabling precise partitions even in overlapping or weak-boundary regions. By replacing sensitive centroid estimates under noise with interpretable granules, the framework improves transitions, reduces membership ambiguity, and improves robustness. The method was benchmarked on six public UCI datasets and real-world production data of sintering process coming from an integrated steelworks. Against FCM, kernel-based FCM, spectral clustering and clustering algorithm based on bidirectional conical information granularity (CBCG), the proposed method achieved the highest average accuracy, Fowlkes-Mallows index, and rand index while retaining competitive rand index values. The main contributions of this paper are as follows: A novel industrial condition identification framework based on rectangular information granules is proposed, where rectangular information granularity is employed to replace the traditional point-based cluster center representation. A robust clustering framework combining weighted granule distance and fuzzy clustering is developed, enhancing clustering accuracy. On real-world production dataset, the proposed method improves accuracy by 22% compared to CBCG and achieves a 5.5% accuracy improvement over the field application method FCM.

铁矿石烧结受高度非线性动力学和多工况控制。该过程的数据表现出噪声和不平衡等特征。传统的聚类方法，如模糊c均值（FCM），往往难以处理诸如噪声、数据不平衡和模糊聚类边界等问题。本文提出了一种集信息颗粒建模、智能优化和模糊聚类于一体的多级聚类框架。与传统的基于点的方法不同，矩形信息颗粒被明确地构建以捕获边界不确定性，随后通过粒子群优化进行优化，提供可解释和自适应的数据抽象。然后引入一种新的加权模糊颗粒距离来聚类优化颗粒，即使在重叠或弱边界区域也能实现精确分区。通过用可解释的颗粒代替噪声下的敏感质心估计，该框架改善了过渡，减少了隶属度模糊，提高了鲁棒性。该方法在6个公共UCI数据集和来自某综合钢厂的烧结过程的实际生产数据上进行了基准测试。与FCM、基于核的FCM、光谱聚类和基于双向圆锥信息粒度（CBCG）的聚类算法相比，该方法在保持竞争的rand指数值的同时，获得了最高的平均准确率、Fowlkes-Mallows指数和rand指数。本文的主要贡献如下：提出了一种新的基于矩形信息颗粒的工业状态识别框架，用矩形信息粒度代替传统的基于点的聚类中心表示；提出了一种结合加权颗粒距离和模糊聚类的鲁棒聚类框架，提高了聚类精度。在实际生产数据集上，与CBCG相比，该方法的精度提高了22%，比现场应用方法FCM的精度提高了5.5%。

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引用次数: 0

A model-free dynamic sliding mode control approach with iterated-integral terms on sliding surface for chemical processes 一种具有滑动面上迭代积分项的无模型动态滑模控制方法

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-05-01 Epub Date: 2026-02-06 DOI: 10.1016/j.conengprac.2026.106821

Marco Herrera , Oscar Camacho , Alvaro Javier Prado-Romo

This paper introduces a novel control approach called Model-Free Dynamic Sliding Mode Control with an Iterated-Integral Sliding Surface (MF-DSMC), designed to improve the control performance of chemical processes characterized by nonlinear dynamics, time-varying behavior, and system uncertainties. The proposed method integrates the robustness of Sliding Mode Control (SMC) with the adaptability of Model-Free Control (MFC), using an iterated-integral sliding surface to enhance transient response. A data-driven ultralocal model is employed in real time to estimate the system’s behavior and adapt the switching gain dynamically. This reduces the dependence on fixed parameters and helps to mitigate chattering effects. The MF-DSMC strategy is validated through two thermal process case studies: (i) a simulated mixing tank with long and varying time delay, and (ii) an experimental setup using the Temperature Control Laboratory (TCLab) platform. The simulation assesses the controller’s robustness and reference tracking under nonlinear and delayed conditions. The experimental setup evaluates its real-time performance. The results show that MF-DSMC achieves improved precision, adaptability, and robustness compared to conventional control methods. In particular, during the TCLab experiments, MF-DSMC obtained the better performance indices in terms of Integral of Absolute Error (IAE), Integral of Squared Error (ISE), and Total Variation of the control signal (TVu), outperforming a classical Model-Free Proportional-Integral (MF-PI) controller.

本文介绍了一种新的控制方法，称为迭代积分滑动面（MF-DSMC）的无模型动态滑模控制，旨在改善具有非线性动力学，时变行为和系统不确定性的化学过程的控制性能。该方法将滑模控制（SMC）的鲁棒性与无模型控制（MFC）的自适应性相结合，利用迭代积分滑动面增强系统的瞬态响应。采用数据驱动的超局部模型实时估计系统行为并动态调整开关增益。这减少了对固定参数的依赖，有助于减轻抖振效应。通过两个热过程案例研究验证了MF-DSMC策略：(i)具有长时间和可变时间延迟的模拟混合槽，以及（ii）使用温度控制实验室（TCLab）平台的实验设置。仿真评估了控制器在非线性和延迟条件下的鲁棒性和参考跟踪性。实验装置评估了其实时性能。结果表明，与传统控制方法相比，MF-DSMC具有更高的精度、适应性和鲁棒性。特别是在TCLab实验中，MF-DSMC在绝对误差积分（IAE）、平方误差积分（ISE）和控制信号总变分（TVu）方面获得了更好的性能指标，优于经典的无模型比例积分（MF-PI）控制器。

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引用次数: 0

Semi-supervised spatio-temporal graph variational autoencoder for enhanced industrial process fault diagnosis under label scarcity 标签稀缺性下增强工业过程故障诊断的半监督时空图变分自编码器

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-05-01 Epub Date: 2026-02-11 DOI: 10.1016/j.conengprac.2026.106831

Mei Tang , Le Yao , Zheren Zhu , Bingbing Shen , Jiusun Zeng , Zhihuan Song

Timely and accurate fault diagnosis is crucial for industrial operational safety, yet conventional methods are constrained by label scarcity, nonlinear dynamics, and spatio-temporal dependencies in process data. This paper proposes a novel Semi-Supervised Spatio-Temporal Graph Variational Autoencoder (SS-STGVAE) to address these issues. The SS-STGVAE integrates three innovative components. First, a dynamic K-nearest neighbors (KNN)-based graph construction mechanism that adaptively captures sensor data similarity and updates topology iteratively is proposed. Second, a spatio-temporal graph convolution network (STGCN) module (stacking temporal and graph convolutions) for synchronous modeling of temporal dynamics and spatial correlations is established. Third, a symmetric graph variational autoencoder (GVAE) with a progressive semi-supervised strategy is presented, which ensures latent-original space consistency, and dynamically balances classification, reconstruction, and Kullback-Leibler divergence losses via incremental unlabeled data introduction. Finally, case studies on two industrial process cases have demonstrated the superiority of the proposed SS-STGVAE that offers a robust solution for label-scarce industrial fault diagnosis.

及时准确的故障诊断对工业运行安全至关重要，但传统的故障诊断方法受到过程数据中标签稀缺性、非线性动力学和时空依赖性的限制。本文提出了一种新的半监督时空图变分自编码器（SS-STGVAE）来解决这些问题。SS-STGVAE集成了三个创新组件。首先，提出了一种基于动态k近邻（KNN）的自适应捕获传感器数据相似度并迭代更新拓扑结构的图构建机制；其次，建立了时空图卷积网络（STGCN）模块（叠加时间卷积和图卷积），用于时间动态和空间相关性的同步建模。第三，提出了一种采用渐进式半监督策略的对称图变分自编码器（GVAE），该算法保证了潜在原始空间的一致性，并通过增量无标记数据引入动态平衡了分类、重构和Kullback-Leibler散度损失。最后，通过对两个工业过程的案例研究，证明了所提出的SS-STGVAE的优越性，为标签稀缺的工业故障诊断提供了一个鲁棒的解决方案。

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引用次数: 0

Robust jumping control of quadruped robots under body and leg disturbances using reinforcement learning with H∞ regularization 基于H∞正则化强化学习的四足机器人身体和腿部扰动鲁棒跳跃控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-10 DOI: 10.1016/j.conengprac.2025.106751

Shuo Xue , Liang Yuan , Kai Lv , Teng Ran , Wendong Xiao , Jianbo Zhang

Quadruped robots rely on jumping ability to traverse discontinuous terrain and complex obstacles, allowing them to perform challenging tasks in dynamic and unpredictable environments. However, jumping control faces multiple challenges, including high-dimensional nonlinear dynamics, underactuation during flight, external disturbances, which make it difficult to ensure stability and robustness. Current reinforcement learning methods usually apply random disturbances only on the body of robot during training to improve jumping robustness. However, due to the high randomness, low accuracy and narrow application scope, the training effect is limited. To address these issues, this study proposes a reinforcement learning framework that systematically introduces disturbances on both the body and legs to improve overall stability. An adaptation module is designed to predict environmental and disturbance information, enhancing the quality of training data. Furthermore, a learnable disturbance generator based on H_∞ regularization is introduced to dynamically generate appropriate disturbances according to the performance of the robot. The learned policy is deployed on a real quadruped robot and evaluated in complex indoor and outdoor environments. Experimental results demonstrate strong robustness and generalization of the learned policy, enabling stable and reliable jumping performance.

四足机器人依靠跳跃能力穿越不连续的地形和复杂的障碍物，使它们能够在动态和不可预测的环境中执行具有挑战性的任务。然而，跳跃控制面临着高维非线性动力学、飞行欠驱动、外部扰动等诸多挑战，难以保证其稳定性和鲁棒性。目前的强化学习方法通常只在训练过程中对机器人身体施加随机扰动，以提高跳跃的鲁棒性。但由于随机性大、准确率低、适用范围窄，训练效果有限。为了解决这些问题，本研究提出了一个强化学习框架，系统地在身体和腿部引入干扰，以提高整体稳定性。设计了自适应模块来预测环境和干扰信息，提高了训练数据的质量。在此基础上，引入了基于H∞正则化的可学习扰动发生器，根据机器人的性能动态产生适当的扰动。将学习到的策略部署在一个真实的四足机器人上，并在复杂的室内和室外环境中进行评估。实验结果表明，该策略具有较强的鲁棒性和泛化性，实现了稳定可靠的跳跃性能。

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引用次数: 0

Adaptive nonlinear model predictive control of monoclonal antibody glycosylation in CHO cell culture CHO细胞培养单克隆抗体糖基化的自适应非线性模型预测控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.conengprac.2025.106731

Yingjie Ma , Jing Guo , Alexis B. Dubs , Krystian Ganko , Richard D. Braatz

N-glycosylation is a critical quality attribute of monoclonal antibodies (mAbs), the dominant class of biopharmaceuticals. Controlling glycosylation remains difficult due to intrinsic pathway complexity, limited online measurements, and a lack of tailored control strategies. This work applies an adaptive nonlinear model predictive control (ANMPC) framework to a fed-batch mAb production process, using a multiscale model that links extracellular conditions to intracellular Golgi reactions to predict glycan profiles. Model parameters are updated online as new measurements arrive, after which a shrinking-horizon optimization computes the control inputs; only the first control move is implemented each cycle. Case studies show that, with a minimal day-1 galactose excitation, ANMPC mitigates model–plant mismatch and achieves up to 130% and 96% higher performance than open-loop optimization and state NMPC, respectively. Under more realistic conditions (partial measurement availability and longer preparation time), ANMPC maintains comparable performance, indicating robustness to practical limitations. Overall, the results demonstrate that ANMPC can actively shape glycan distributions in silico and offers a viable path toward closed-loop control of mAb glycosylation.

n -糖基化是单克隆抗体（mab）的关键质量属性，单克隆抗体是生物制药的主导类别。由于内在途径的复杂性、有限的在线测量和缺乏定制的控制策略，控制糖基化仍然很困难。这项工作将自适应非线性模型预测控制（ANMPC）框架应用于补批单抗生产过程，使用将细胞外条件与细胞内高尔基反应联系起来的多尺度模型来预测聚糖谱。当新的测量值到达时，在线更新模型参数，然后通过缩界优化计算控制输入；每个周期只执行第一个控制动作。案例研究表明，在1天半乳糖激励最小的情况下，ANMPC减轻了模型与工厂的不匹配，比开环优化和状态NMPC的性能分别提高了130%和96%。在更现实的条件下（部分测量可用性和更长的制备时间），ANMPC保持相当的性能，表明对实际限制的鲁棒性。总之，结果表明，ANMPC可以积极地塑造聚糖在硅中的分布，并为单克隆抗体糖基化的闭环控制提供了可行的途径。

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引用次数: 0

Benchmark vehicle suspension data based on ISO 8608 road profiles 基于ISO 8608道路轮廓的基准车辆悬架数据

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.conengprac.2025.106755

Mathias Foo , Ai Hui Tan

Ride comfort is a key factor in passenger safety and is largely determined by the suspension system of a vehicle. Although mechanical active suspension systems have greatly improved ride quality, the move towards electronically controlled active suspensions—driven by rapid advances in vehicle technology—requires more sophisticated engineering solutions. This challenge is made even greater by the increasing variability of modern road infrastructure. To design and validate such solutions, suspension systems need to be tested across a wide variety of road surface profiles. Understanding the system’s limitations under different conditions is crucial before developing and evaluating control strategies. For this reason, standardised road profiles that accurately represent different types of terrain are essential. This paper presents a benchmark dataset for vehicle suspension systems based on ISO-compliant road profiles. The dataset has been developed to support researchers working on suspension parameter identification, control algorithm design, and the study of nonlinear suspension behaviour. To illustrate its value, a benchmark comparison of system identification models using the dataset is provided. The data containing ISO road profiles and measured suspension displacements, along with codes for modelling and visualisation, is freely available at https://doi.org/10.5281/zenodo.17242919

乘坐舒适性是乘客安全的关键因素，在很大程度上取决于车辆的悬架系统。虽然机械主动悬架系统大大提高了乘坐质量，但在汽车技术快速发展的推动下，向电子控制主动悬架的转变需要更复杂的工程解决方案。现代道路基础设施的不断变化使这一挑战更加严峻。为了设计和验证这些解决方案，悬架系统需要在各种路面上进行测试。在制定和评估控制策略之前，了解系统在不同条件下的局限性至关重要。因此，准确表示不同类型地形的标准化道路轮廓是必不可少的。本文提出了一个基于iso标准道路轮廓的汽车悬架系统基准数据集。该数据集的开发是为了支持研究人员对悬架参数识别、控制算法设计和非线性悬架行为的研究。为了说明其价值，提供了使用该数据集的系统识别模型的基准比较。包含ISO道路轮廓和测量的悬架位移的数据，以及建模和可视化代码，可在https://doi.org/10.5281/zenodo.17242919免费获得

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引用次数: 0

Robust trajectory tracking control for quadrotors based on an enhanced extended state observer 基于增强扩展状态观测器的四旋翼飞行器鲁棒轨迹跟踪控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-15 DOI: 10.1016/j.conengprac.2025.106725

Salvatore Pedone, Adriano Fagiolini

In this paper the robust trajectory tracking control problem for a quadrotor aircraft is addressed by utilizing the estimates from an Enhanced Extended State Observer (EESO). More specifically, first, the quadrotor dynamics is reformulated by decoupling the known linear terms from the unknown and nonlinear ones and by modeling the latter as new additional state variables. Secondly, by exploiting the information deriving from the output and input vectors, respectively, an EESO is derived allowing an asymptotic estimation of the state vector even when the rate of change of the unknown disturbances is fast and not negligible. Finally, on the basis of the EESO estimates, a robust trajectory tracking controller is designed, ensuring the asymptotic convergence of system state trajectories to the desired ones. The full asymptotic stability is demonstrated analytically. Simulation results on a quadrotor model through a high-fidelity low-altitude simulation environment are shown to illustrate the efficiency of the proposed method also with respect to existing solution (Extended State Observer based Control).

本文利用增强扩展状态观测器（EESO）的估计来解决四旋翼飞行器的鲁棒轨迹跟踪控制问题。更具体地说，首先，通过将已知的线性项与未知和非线性项解耦并将后者建模为新的附加状态变量来重新表述四旋翼动力学。其次，通过利用分别来自输出和输入向量的信息，推导出EESO，即使在未知干扰的变化率很快且不可忽略的情况下，也允许对状态向量进行渐近估计。最后，在EESO估计的基础上，设计了鲁棒轨迹跟踪控制器，保证了系统状态轨迹向期望状态轨迹渐近收敛。用解析方法证明了系统的完全渐近稳定性。通过高保真低空仿真环境对四旋翼模型的仿真结果表明，该方法相对于现有的解决方案（基于扩展状态观测器的控制）也是有效的。

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引用次数: 0

Evaluation of servo fault status and fault-tolerant control for heavy-legged robots under concurrent velocity sensor failures 速度传感器并发故障下的大腿机器人伺服故障状态评估与容错控制

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.conengprac.2026.106761

Shaoxun Liu , Shiyu Zhou , Mohamed Abdullah , Zhengsheng Liu , Hui Zhang , Rongrong Wang

The reliability of actuators and sensors is critical for the safe operation of heavy-legged robots (HLRs), yet few schemes handle concurrent actuator and sensor faults under model uncertainty. This study presents an integrated fault-tolerant control architecture that incorporates permanent magnet synchronous motor (PMSM) phase currents into the trajectory tracking loop. A complementary filter-based observer is developed to estimate HLR velocities and model residuals, while a fault gain loss estimator (FGLE) quantifies servo fault severity from PMSM current-controller residuals. An embedded radial basis function network further determines whether the HLR retains its fault-tolerant capability. Leveraging the estimated servo status, a field-oriented fault-tolerant controller is formulated to (1) seamlessly coordinate PMSM and HLR control, (2) sustain precise trajectory tracking under actuator and sensor failures, and (3) execute a controlled stop when driving capability is lost, thereby mitigating economic loss. Experimental validation on an electric-cylinder-driven HLR demonstrates that the proposed framework reduces RMSE and MAE by 11.7% and 10.2%, respectively, compared with conventional integrated frameworks, while ensuring safe shutdown without secondary damage.

执行器和传感器的可靠性对大腿机器人的安全运行至关重要，但在模型不确定性下处理执行器和传感器并发故障的方案很少。该研究提出了一种集成容错控制体系结构，将永磁同步电机（PMSM）相电流集成到轨迹跟踪回路中。基于互补滤波器的观测器用于估计HLR速度和模型残差，而故障增益损失估计器（FGLE）从PMSM电流控制器残差中量化伺服故障严重程度。嵌入式径向基函数网络进一步决定HLR是否保留其容错能力。利用估计的伺服状态，制定了面向现场的容错控制器，以(1)无缝协调PMSM和HLR控制，(2)在执行器和传感器故障下保持精确的轨迹跟踪，(3)在失去驱动能力时执行受控停止，从而减轻经济损失。在电动气缸驱动的HLR上进行的实验验证表明，与传统的集成框架相比，该框架的RMSE和MAE分别降低了11.7%和10.2%，同时确保了安全停机，没有二次损坏。

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引用次数: 0

A robust fault-tolerant control algorithm for GPS-denied mini quadrotors using PID-TinyMPC and visual-inertial odometry 基于PID-TinyMPC和视觉惯性里程计的gps拒绝迷你四旋翼鲁棒容错控制算法

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.conengprac.2026.106779

Emre Çintaş , Barış Özyer

Fault-tolerant control (FTC) is crucial for ensuring the safety and reliability of autonomous quadrotors, especially in scenarios involving rotor failures. This paper presents a hybrid control architecture that combines a PID-based outer-loop controller with a TinyMPC-based inner-loop controller, integrated with visual-inertial odometry (VIO) for real-time state estimation. The proposed method enables a mini quadrotor to maintain stable flight and trajectory tracking even under rotor failure conditions, using only onboard sensors (IMU, barometer and monocular camera) without relying on external positioning systems such as GPS and VICON. The outer-loop PID controller handles position control at a lower frequency, while the inner-loop TinyMPC operates at a higher frequency to manage the fast-changing attitude dynamics. This design reduces computational overhead while maintaining spatial-temporal stability and precision. Experimental results demonstrate the effectiveness of the proposed method in real-world scenarios, where the quadrotor successfully maintains hovering under varying yaw rates and rotor speed reduction conditions. The proposed low-cost, computationally efficient solution addresses a significant gap in the literature by providing a robust FTC approach that is feasible for microcontrollers and resource-constrained platforms. The source code and some flight videos are publicly available at: https://github.com/emrecintas/fault_tolerant_control.

容错控制（FTC）对于确保自主四旋翼飞行器的安全性和可靠性至关重要，特别是在涉及转子故障的情况下。本文提出了一种混合控制体系结构，该结构结合了基于pid的外环控制器和基于tinympc的内环控制器，并集成了用于实时状态估计的视觉惯性里程计（VIO）。所提出的方法使小型四旋翼即使在转子故障条件下也能保持稳定的飞行和轨迹跟踪，仅使用机载传感器（IMU，气压计和单目摄像机），而不依赖外部定位系统（如GPS和VICON）。外环PID控制器以较低的频率处理位置控制，而内环TinyMPC以较高的频率工作以管理快速变化的姿态动力学。这种设计在保持时空稳定性和精度的同时减少了计算开销。实验结果证明了该方法在实际场景中的有效性，四旋翼飞行器在不同的偏航率和旋翼减速条件下都能成功保持悬停。提出的低成本，计算效率高的解决方案通过提供对微控制器和资源受限平台可行的强大的FTC方法来解决文献中的重大差距。源代码和一些飞行视频可以在：https://github.com/emrecintas/fault_tolerant_control上公开获得。

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引用次数: 0

A review of noise-aware path planning for urban drone operations 城市无人机作业噪声感知路径规划研究综述

IF 4.6 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.conengprac.2025.106750

Yinuo Wang , Nan Zhang , Xun Huang

The accelerating integration of drones into urban air mobility (UAM) has sparked concerns about noise pollution and its consequences on public acceptance and regulatory frameworks. This review examines the role of noise-aware air traffic management strategies in facilitating the harmonious incorporation of drones into the low-altitude economy. First, we examine traditional noise mitigation practices within conventional aviation and assess their suitability for drone applications. Next, we offer an overview of drone noise measurement techniques and psychoacoustic metrics to facilitate a more nuanced understanding for drone noise modeling. To obtain deep insights into noise-aware path planning, we outline general optimization methods before focusing specifically on how noise-related factors can be integrated into the planning process. Key advances in noise-related loss functions, optimization algorithms, and unique application scenarios are evaluated. Finally, we identify the potential challenges of implementing noise-aware UAM and propose several possible future research directions in noise-aware path planning.

无人机与城市空中交通（UAM）的加速融合引发了人们对噪音污染及其对公众接受度和监管框架的影响的担忧。本综述探讨了噪声感知空中交通管理策略在促进无人机和谐融入低空经济中的作用。首先，我们研究了传统航空中的传统降噪做法，并评估了它们对无人机应用的适用性。接下来，我们提供无人机噪声测量技术和心理声学指标的概述，以促进更细致入微的理解无人机噪声建模。为了深入了解噪声感知路径规划，我们概述了一般的优化方法，然后特别关注如何将噪声相关因素集成到规划过程中。评估了噪声相关损失函数、优化算法和独特应用场景的关键进展。最后，我们确定了实现噪声感知UAM的潜在挑战，并提出了噪声感知路径规划的几个可能的未来研究方向。

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引用次数: 0