ISA transactions最新文献_第7页

Remaining useful life prediction with limited run-to-failure data: A Bayesian ensemble approach combining mode-dependent RVM and similarity. 利用有限的运行至故障数据预测剩余使用寿命：结合模式依赖性 RVM 和相似性的贝叶斯集合方法。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-16 DOI: 10.1016/j.isatra.2024.11.023

Zhuyi Li, Hao Zheng, Xianbo Xiang, Shuai Liu, Yiming Wan

{"title":"Remaining useful life prediction with limited run-to-failure data: A Bayesian ensemble approach combining mode-dependent RVM and similarity.","authors":"Zhuyi Li, Hao Zheng, Xianbo Xiang, Shuai Liu, Yiming Wan","doi":"10.1016/j.isatra.2024.11.023","DOIUrl":"10.1016/j.isatra.2024.11.023","url":null,"abstract":"Accurate prediction of remaining useful life (RUL) is crucial for predictive maintenance of industrial systems. Although data-driven RUL prediction methods have received considerable attention, they typically require massive run-to-failure (R2F) data which is often unavailable in practice. If not properly addressed, training with a limited number of R2F trajectories not only leads to large errors in RUL prediction, but also causes difficulty in quantifying the prediction uncertainty. To address the above challenge, this paper proposes a Bayesian ensemble RUL prediction method that combines mode-dependent relevance vector machine (RVM) and trajectory similarity. Firstly, the proposed approach clusters historical R2F trajectories of unequal lengths into different degradation modes, and constructs RVM and similarity based predictions with improved accuracy by using mode-dependent libraries of kernel functions and similar trajectories. Secondly, the proposed Bayesian ensemble scheme fuses the RVM and similarity based predictions, and quantifies the associated prediction uncertainty even though the number of historical R2F trajectories are limited. In two case studies involving bearings and batteries, using only 11 and 16 R2F trajectories as training data, respectively, the proposed method reduces the mean absolute percentage error of RUL prediction by more than 20% compared to three existing methods.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"307-319"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive robust motion control for hydraulic load sensitive systems considering displacement dynamic compensation. 考虑位移动态补偿的液压负载敏感系统的自适应鲁棒运动控制。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-07 DOI: 10.1016/j.isatra.2024.10.019

Zhongyi Qiu, Xiaochao Liu, Zhenyu Wang, Xinghua Chen, Rui Nie

{"title":"Adaptive robust motion control for hydraulic load sensitive systems considering displacement dynamic compensation.","authors":"Zhongyi Qiu, Xiaochao Liu, Zhenyu Wang, Xinghua Chen, Rui Nie","doi":"10.1016/j.isatra.2024.10.019","DOIUrl":"10.1016/j.isatra.2024.10.019","url":null,"abstract":"Hydraulic load-sensitive systems (HLSS) are widely used for high power density and energy efficiency. This study introduces an adaptive, energy-efficient HLSS with a valve-controlled variable motor. The system faces challenges from non-linearities, including internal higher-order dynamics due to displacement changes and external unknown disturbances, which hinder precision applications. To address this issue, this study explores HLSS principles to develop an accurate system model. Subsequently, an adaptive robust motion control that considers displacement compensation (DCARC) is proposed using the established model. DCARC can learn unknown parameters online and compensate the model more accurately to improve control accuracy. Experiments show that considering the higher order dynamic effects caused by displacement in the system can improve model accuracy and effectively reduce the burden of parameter adaptation and robust feedback terms. High-precision and energy-efficient HLSS motion is verified and realized in the study. The control accuracy of DCARC is 19.4% higher than that of conventional adaptive robust control (ARC). Under experimental conditions, the proposed system can improve energy efficiency by up to five times compared to valve-controlled fixed displacement motor systems (VFDS).","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"490-500"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quadrotor trajectory tracking using combined stochastic model-free position and DDPG-based attitude control. 利用组合式无随机模型位置控制和基于 DDPG 的姿态控制进行四旋翼飞行器轨迹跟踪。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-08 DOI: 10.1016/j.isatra.2024.11.007

Roujin Mousavifard, Khalil Alipour, Mohamad Amin Najafqolian, Payam Zarafshan

引用次数: 0

A performance degradation assessment method for complex electromechanical systems based on adaptive evidential reasoning rule. 基于自适应证据推理规则的复杂机电系统性能退化评估方法。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-17 DOI: 10.1016/j.isatra.2024.11.026

Bangcheng Zhang, Shuo Gao, Shiyuan Lv, Nan Jia, Jie Wang, Bo Li, Guanyu Hu

{"title":"A performance degradation assessment method for complex electromechanical systems based on adaptive evidential reasoning rule.","authors":"Bangcheng Zhang, Shuo Gao, Shiyuan Lv, Nan Jia, Jie Wang, Bo Li, Guanyu Hu","doi":"10.1016/j.isatra.2024.11.026","DOIUrl":"10.1016/j.isatra.2024.11.026","url":null,"abstract":"The evidence reasoning (ER) rule has been widely used in various fields to deal with both quantitative and qualitative information with uncertainty. However, when analyzing dynamic systems, the importance of various indicators frequently changes with time and working conditions, such as performance degradation assessment of complex electromechanical systems, and the weights of the traditional evidence reasoning rules cannot be appropriately adjusted. To solve this problem, this paper proposes an adaptive evidence reasoning (AER) rule that can adjust weights according to different times and working conditions. The AER rule has two unique features: adaptive weight operation under time division and adaptive weight operation under working-condition division, which are used to solve the problem of dynamic weight adjustment under different times and working conditions. The CMA-ES algorithm is used to optimize the model parameters. Two case studies of performance degradation assessment are established to prove the advantage of the AER rule: a computer numerical control experiment and a simulation experiment of turbofan aeroengine. The results verify the effectiveness and practicability of the proposed method.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"408-422"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142735431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning-based optimal boundary control for parabolic distributed parameter system with actuator dynamics. 具有作动器动力学的抛物型分布参数系统基于学习的最优边界控制。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-18 DOI: 10.1016/j.isatra.2024.11.013

Jingyi Sun, Biao Luo, Xiaodong Xu, Chunhua Yang

{"title":"Learning-based optimal boundary control for parabolic distributed parameter system with actuator dynamics.","authors":"Jingyi Sun, Biao Luo, Xiaodong Xu, Chunhua Yang","doi":"10.1016/j.isatra.2024.11.013","DOIUrl":"10.1016/j.isatra.2024.11.013","url":null,"abstract":"Considering actuator dynamics, we investigate a coupled system of parabolic partial differential equations (PDEs) and ordinary differential equations (ODEs), developing a data-driven boundary optimal controller based on iterative learning. Notably, the boundary input appears in the ODE-style actuator dynamics, making the boundary condition reduction quite difficult. Optimizing infinite-dimensional performance indexes in coupled Hilbert spaces is not a trivial task. This work is the first to solve the optimal control problem for a coupled PDE-ODE system with actuator dynamics under Neumann boundary conditions. We equivalently reformat the coupled PDE-ODE system into a system with homogeneous boundary conditions and then derive its singular perturbation form in an infinite-dimensional space. Subsequently, by constructing critic and actor networks, we design a novel model-free iterative learning optimal control algorithm where weighted residual techniques are used. The algorithm uses a rich set of arbitrary control policies rather than limiting to evaluation policies, enhancing the exploration capability of the learning algorithm and relaxing the requirement for persistent excitation conditions. Furthermore, the uniformly asymptotic stability of the closed-loop coupled system is demonstrated in the infinite-dimensional Hilbert space for each learning iteration, not only for the final one. Finally, the effectiveness of the proposed approach is verified by simulations on the diffusion-reaction process.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"228-239"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142751123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

H_∞ fault-tolerant fuzzy intermittent control for nonlinear hyperbolic PDE systems with multiple delays and actuator failures. 多时滞非线性双曲型PDE系统的H∞容错模糊间歇控制。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-25 DOI: 10.1016/j.isatra.2024.11.017

Xu Zhang, Xuan Gao, Zi-Peng Wang, Biao Luo, Ke-Zhen Han, Xue-Hua Yan

引用次数: 0

Real-time identification of multi-component periodic signals using Online Harmonics Extraction Approach. 利用在线谐波提取法实时识别多成分周期信号。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-12-04 DOI: 10.1016/j.isatra.2024.11.033

Qingquan Liu, Xin Huo, Kang-Zhi Liu, Minghui Chu, Hui Zhao

引用次数: 0

Distributed adaptive safe fault-tolerant control for nonlinear systems based on Barrier function. 基于屏障函数的非线性系统分布式自适应安全容错控制。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-19 DOI: 10.1016/j.isatra.2024.11.011

Min Zhang, Xiangbin Liu, Hongye Su

引用次数: 0

Adaptive RISE-based tracking control of uncertain nonlinear systems: A FAS approach. 基于 RISE 的不确定非线性系统自适应跟踪控制：FAS 方法

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-07 DOI: 10.1016/j.isatra.2024.10.034

Zhijun Chen, Guangren Duan

{"title":"Adaptive RISE-based tracking control of uncertain nonlinear systems: A FAS approach.","authors":"Zhijun Chen, Guangren Duan","doi":"10.1016/j.isatra.2024.10.034","DOIUrl":"10.1016/j.isatra.2024.10.034","url":null,"abstract":"A fully actuated system (FAS) approach integrated with adaptive robust integral of the sign of the error (ARISE) feedback control strategy is proposed for multi-input multi-output nonlinear systems in the presence of both external disturbances and parametric uncertainties. Owing to an inability to eliminate unmeasured disturbances and model inaccuracies simultaneously, the existing results based on the FAS approaches are typically limited to the uniformly ultimate boundedness of the tracking errors. To achieve the asymptotic tracking performance confronted with parametric uncertainties and time-varying disturbances, an ARISE feedback controller with desired compensation is synthesized to suppress the adverse effects arising from nonlinearity and uncertainty of the system. The improvements compared to the traditional RISE feedback control are attributed to two aspects: (i) the feedback gains in the RISE term are adjustable-online without having to know the prior bounds of disturbances and their time derivatives; (ii) a desired compensation-based adaptive feedforward term, primarily employing the desired trajectories in place of the measured states, could weaken the underlying interaction between the adaptive compensation and robustness part. A rigorous stability analysis is provided to demonstrate that the system state can asymptotically track a bounded desired trajectory in spite of bounded disturbances and parametric uncertainties. Comparative simulations on an under-actuated planar manipulator, possessing an equivalent multi-order FAS model, have been conducted to verify the effectiveness and merits of the developed controller. Experimental validation on a two-wheeled self-balancing robot is also provided to show the feasibility of the proposed approach.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"501-512"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid model using bond graph-TCN network and event triggered predictive control of pH neutralization process. 结合键合图- tcn网络和事件触发预测控制pH中和过程的混合模型。

ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-17 DOI: 10.1016/j.isatra.2024.11.025

Joanofarc Xavier, M A Henry Barath, Sanjib Kumar Patnaik, Rames C Panda, Atanu Panda

{"title":"Hybrid model using bond graph-TCN network and event triggered predictive control of pH neutralization process.","authors":"Joanofarc Xavier, M A Henry Barath, Sanjib Kumar Patnaik, Rames C Panda, Atanu Panda","doi":"10.1016/j.isatra.2024.11.025","DOIUrl":"10.1016/j.isatra.2024.11.025","url":null,"abstract":"The pH neutralization process is a concrete decisive unit in major reactor units of industrial process control loops. This article presents a new fuzzy-based hybrid 'Bond Graph-Temporal Convolution Network' (BG-TCN) model, structured for the convoluted dynamics of a real-time pH neutralization unit, known for its complexity and high nonlinearity. The TCN scheme suggested in this article, exploits a one-dimensional causal convolution strategy within a residual learning framework to execute dilated causal convolutions through time series data analysis. Conversely, Bond Graph (BG) is a graphical tool, designed on an energy-centric approach, to represent energy transfer and interactions across different compartments of the nonlinear pH neutralization system. Furthermore, a linguistic fuzzy rule-based inference system is encompassed to handle uncertainties from BG and TCN models, allowing smooth integration and flexible transition between these two approaches. Additionally, the performance of the hybrid BG-TCN model is assessed against the individual TCN and BG models in a Python environment. On top of that, this article also envisions an event-triggered predictive control utilizing a fuzzy event handler mechanism to demonstrate the efficacy of the proposed hybrid BG-TCN in attaining precise set point tracking for closed-loop servo and regulatory problems.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":"639-654"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0