Control Engineering Practice最新文献

A novel model predictive dynamic adaptive impedance control for robotic force tracking on complex surfaces 一种新型模型预测动态自适应阻抗控制用于复杂表面机器人力跟踪

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-19 DOI: 10.1016/j.conengprac.2025.106398

Yilin Mu, Lai Zou, Ziling Wang, Jiantao Li, Linlin Jiang, Wenxi Wang

{"title":"A novel model predictive dynamic adaptive impedance control for robotic force tracking on complex surfaces","authors":"Yilin Mu, Lai Zou, Ziling Wang, Jiantao Li, Linlin Jiang, Wenxi Wang","doi":"10.1016/j.conengprac.2025.106398","DOIUrl":"10.1016/j.conengprac.2025.106398","url":null,"abstract":"<div><div>The time-varying nature and complexity of environmental stiffness make it difficult to achieve accurate and stable tracking of normal contact force on complex surfaces in robotic belt grinding. The more complex the contact environment, the higher the requirements for robotic perception and self-regulation capabilities in relation to the environment. To address this issue, a novel model predictive dynamic adaptive impedance control algorithm (MPRPO-DAIC) is proposed to improve the accuracy of robotic force tracking in complex contact environments. This control strategy consists of a dynamic adaptive impedance control algorithm integrated with a model predictive control framework. The dynamic adaptive impedance control enhances the robustness of adaptive impedance controller (AIC) by introducing a dynamic observer term. Additionally, the rolling parameter optimization algorithm enables real-time optimization of key parameters within the dynamic observer. Subsequently, through the combination of dynamic adaptive impedance control and model predictive control, the robotic velocity compensation value is calculated by solving a quadratic programming problem. Finally, the velocity compensation value is integrated and sent to the robotic end-effector, enabling stable tracking of contact forces in complex surfaces. The simulation and experimental results of force tracking on complex surfaces validate the superiority of the proposed control strategy. The simulation results show that MPRPO-DAIC exhibits optimal force control performance in complex tracking environments. In the force tracking experiments, MPRPO-DAIC improved the force control accuracy by 37.25% and 44.90% compared to AIC on surfaces with large deformation and high-frequency variation, respectively.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"163 ","pages":"Article 106398"},"PeriodicalIF":5.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084489","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

Predefined-time prescribed performance fault-tolerant control for robotic manipulator trajectory tracking 机器人机械臂轨迹跟踪的预定义时间规定性能容错控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-19 DOI: 10.1016/j.conengprac.2025.106397

Jianjun Zhang , Manjiang Xia , Zhonghua Wu , Shasha Li , Weidong Liu

{"title":"Predefined-time prescribed performance fault-tolerant control for robotic manipulator trajectory tracking","authors":"Jianjun Zhang , Manjiang Xia , Zhonghua Wu , Shasha Li , Weidong Liu","doi":"10.1016/j.conengprac.2025.106397","DOIUrl":"10.1016/j.conengprac.2025.106397","url":null,"abstract":"<div><div>This paper proposes a predefined-time terminal sliding mode prescribed performance control (PTTSMPPC) scheme to address the challenges of bounded external disturbances, model parameter uncertainties, and the uncertainty of traditional stability tracking time in robotic manipulator trajectory tracking control. To mitigate the singularity problem caused by actuator saturation, which often leads to tracking errors exceeding the prescribed performance boundaries in conventional prescribed performance control, an adaptive method for adjusting the performance boundaries is introduced. The novel designed terminal sliding mode surface (TSMS) is continuous and non-singular, ensuring the system’s strong robustness and effectively handling external disturbances and model uncertainties. The global stability of the system within the predefined time is rigorously demonstrated based on Lyapunov stability theory. Simulation and experimental results verify that the proposed PTTSMPPC method achieves superior transient performance and steady-state accuracy, confirming its feasibility and effectiveness.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"163 ","pages":"Article 106397"},"PeriodicalIF":5.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084488","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

Port-Hamiltonian formulation and stabilizing controller for a liquid propelled rocket engine 液体火箭发动机的波特-哈密顿公式及稳定控制器

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-17 DOI: 10.1016/j.conengprac.2025.106389

Jules Gibart , Hélène Piet-Lahanier , Francois Farago

引用次数: 0

Finite-control-set economic model predictive control for a DC/AC inverter 直流/交流逆变器的有限控制集经济模型预测控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-17 DOI: 10.1016/j.conengprac.2025.106385

Xiaobing Kong , Pengyu Zhang , Lele Ma , Zheng Zhu , Xiangjie Liu , Kwang Y. Lee

{"title":"Finite-control-set economic model predictive control for a DC/AC inverter","authors":"Xiaobing Kong , Pengyu Zhang , Lele Ma , Zheng Zhu , Xiangjie Liu , Kwang Y. Lee","doi":"10.1016/j.conengprac.2025.106385","DOIUrl":"10.1016/j.conengprac.2025.106385","url":null,"abstract":"<div><div>Finite-control-set model predictive control (FCS-MPC) is an effective approach for controlling modern power electronics. The three-level sparse neutral point clamped inverter (3L-SNPCI) fulfills the task of converting DC power into the desired three-phase AC power in high-renewable-penetration power systems. The stable and economic operation of the 3L-SNPCI is crucial to the security and reliability of renewable energy grid connection. Controlling of 3L-SNPCI is quite challenging, due to the strong nonlinearity and the discrete feasible region caused by the finite control set. In this paper, a stable economic model predictive control scheme is developed to achieve the key tasks of current tracking, neutral point voltage balance, and inverter economic performance by directly incorporating the economic indices into the controller design. The non-convex optimization problem caused by the inverter nonlinearity is transformed into a convex one with linear inequality constraints by employing the Big-M method. The bounded stability is indirectly guaranteed with the dynamic of the inverter control system approximating that of a stabilized continuous linear time-invariant system sharing the same parameters. Simulation and experiment concerning both the steady-state and transient-state conditions with different disturbance are presented to show the effectiveness and robustness of the proposed controller.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"163 ","pages":"Article 106385"},"PeriodicalIF":5.4,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071608","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

A natural indirect adaptive controller for a satellite-mounted manipulator 星载机械臂的自然间接自适应控制器

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-16 DOI: 10.1016/j.conengprac.2025.106395

Jacopo Giordano , Angelo Cenedese , Andrea Serrani

引用次数: 0

BKMPC-ESO: A data-driven bilinear model predictive control framework for soft robots with unknown nonlinear dynamics compensation BKMPC-ESO：具有未知非线性动力学补偿的软机器人数据驱动双线性模型预测控制框架

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-14 DOI: 10.1016/j.conengprac.2025.106390

Shengchuang Guan , Zhaobing Liu

{"title":"BKMPC-ESO: A data-driven bilinear model predictive control framework for soft robots with unknown nonlinear dynamics compensation","authors":"Shengchuang Guan , Zhaobing Liu","doi":"10.1016/j.conengprac.2025.106390","DOIUrl":"10.1016/j.conengprac.2025.106390","url":null,"abstract":"<div><div>In this paper, we introduce a novel control framework, termed BKMPC-ESO, which integrates bilinear Koopman model predictive control (BKMPC) with an extended state observer (ESO) for the modeling and control of soft robots. This framework specifically addresses the challenges posed by modeling errors and unknown disturbances, which often degrade the control performance of soft robots. It leverages the data-driven bilinear Koopman model to merge the computational efficiency of linear models with the predictive precision of nonlinear models, thereby adapting to the dynamics of diverse systems. Furthermore, the ESO is incorporated for real-time estimation of modeling errors and external disturbances, with these estimates being dynamically compensated within the MPC. This approach effectively mitigates the limitations of the offline bilinear Koopman model in capturing real-time parameter variations and external disturbances, enhancing the system’s control precision. Notably, the proposed BKMPC approach guarantees recursive feasibility and stability across an extended prediction horizon, with the stability of the ESO being rigorously validated through theoretical analysis. The efficacy of our framework is exemplified through its application on a three-dimensional (3D) soft manipulator. It is able to adeptly track a variety of reference trajectories, ranging from simple to complex, thereby highlighting the framework’s potential to significantly enhance the performance capabilities of soft robotic systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106390"},"PeriodicalIF":5.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942280","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

Simplicial complexes graph convolution networks with higher-order features learning for limited samples diagnosis 有限样本诊断中具有高阶特征学习的简单复图卷积网络

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-13 DOI: 10.1016/j.conengprac.2025.106391

Xian-Jie Zhang , Hai-Feng Zhang , Kai Zhong , Xiao-Ming Zhang

{"title":"Simplicial complexes graph convolution networks with higher-order features learning for limited samples diagnosis","authors":"Xian-Jie Zhang , Hai-Feng Zhang , Kai Zhong , Xiao-Ming Zhang","doi":"10.1016/j.conengprac.2025.106391","DOIUrl":"10.1016/j.conengprac.2025.106391","url":null,"abstract":"<div><div>With the advancement of industrial automation, there is an increasing focus on research concerning limited fault samples. Although meta-learning and other methods can address this issue, they often necessitate the incorporation of additional data and are unable to directly diagnose faults using only unlabeled data along with a small amount of labeled data. In response, this article proposes the use of simplicial complexes graph convolutional networks for fault diagnosis, which simultaneously account for both higher-order and lower-order topological structures among samples. This approach effectively addresses the challenge of limited samples by extracting relevant information from unlabeled data without the need to introduce new knowledge. Initially, simplices of varying dimensions are employed within a constructed simple graph to represent different relationships among samples. Subsequently, the simplicial complexes convolutional network is introduced to capture the higher-order information, while the graph convolutional network is utilized to obtain the lower-order information. The combined feature information is then input into a classifier for fault diagnosis. Finally, experiments conducted on two datasets characterized by small sample sizes or imbalanced samples demonstrate the method’s commendable diagnostic performance, as well as its robustness and practicality.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106391"},"PeriodicalIF":5.4,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936555","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

Enhancing trajectory tracking and energy efficiency in Pneumatic Servo Translational Parallel Manipulator with Frac-SMC-RFESO Control 采用fracc - smc - rfeso控制提高气动伺服平移并联机器人的轨迹跟踪和能效

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-13 DOI: 10.1016/j.conengprac.2025.106372

Lian-Wang Lee , Jin-Yu Yang , I-Hsum Li

{"title":"Enhancing trajectory tracking and energy efficiency in Pneumatic Servo Translational Parallel Manipulator with Frac-SMC-RFESO Control","authors":"Lian-Wang Lee , Jin-Yu Yang , I-Hsum Li","doi":"10.1016/j.conengprac.2025.106372","DOIUrl":"10.1016/j.conengprac.2025.106372","url":null,"abstract":"<div><div>Pneumatic-driven systems often face significant energy consumption challenges, primarily due to compressed air leakage and inefficient utilization. To address these issues, this paper presents a comprehensive solution encompassing both hardware and software designs for a Pneumatic Servo Translational Parallel Manipulator (PS-TPM). On the software side, the proposed energy-efficient controller, Frac-SMC-RFESO, integrates fractional-order sliding mode control with a reduced fractional-order extended state observer (RFESO) to optimize the PS-TPM’s performance. This integration endows the Frac-SMC-RFESO with exceptional adaptability, enabling it to effectively manage the system’s complex dynamics and nonlinearities while minimizing energy consumption. Furthermore, by utilizing the RFESO, the controller estimates system uncertainties and disturbances within the PS-TPM, further enhancing trajectory tracking performance. In its mechanical design, the PS-TPM incorporates double-acting magnetic rodless cylinders paired with proportional directional control valves, improving sealing to prevent air leakage and thereby enhancing energy efficiency. Experimental results highlight the exceptional performance of the Frac-SMC-RFESO controller, achieving superior trajectory tracking while reducing energy consumption by 16% to 47% compared to the RLESO-SMC (an integer-order sliding mode controller with a reduced-order linear extended state observer), LADRC (a linear active disturbance rejection controller), and the PID controller.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106372"},"PeriodicalIF":5.4,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936554","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

Model predictive control of high moisture extrusion cooking 高水分挤压蒸煮的模型预测控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-12 DOI: 10.1016/j.conengprac.2025.106387

Adrian Ticǎ , Vivek S. Pinnamaraju , Eric Stirnemann , Erich J. Windhab

{"title":"Model predictive control of high moisture extrusion cooking","authors":"Adrian Ticǎ , Vivek S. Pinnamaraju , Eric Stirnemann , Erich J. Windhab","doi":"10.1016/j.conengprac.2025.106387","DOIUrl":"10.1016/j.conengprac.2025.106387","url":null,"abstract":"<div><div>High Moisture Extrusion Cooking (HMEC) has become a promising technology for producing plant-based meat alternatives. By using HMEC, food manufacturers can create meat-like textures from plant proteins, offering a sustainable solution with reduced carbon footprint to consumers. However, at the current stage of development, the automation level in HMEC is insufficient to ensure operational autonomy, reliability, and product quality expected by industry demands. This paper presents a predictive control framework designed to transform experience-based handled HMEC into a more reliable process operation, improving its production performance and facilitating industrial up-scaling. The proposed control structure is hierarchical, comprising two layers. At the upper layer, a model predictive control (MPC) algorithm determines the optimal set-points for the controllers at the lower layer. The predictive framework is built on the existing HMEC control architecture and can be further extended to achieve fully optimized production. Leveraging linear dynamic models, the approach mainly focuses on the protein melt control aiming to enhance production performance by minimizing the tracking error of process quantities correlated to product quality. The practical feasibility of the designed control solution has been proven on a pilot-scale extruder. Validation results have shown improved operational stability and reproducibility, while effectively tracking set-points for consistent meat-like fibrous structure formation and desired textural characteristics.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106387"},"PeriodicalIF":5.4,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936553","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

High efficiency DC–DC converter for renewable energy integration and energy storage applications: A review of topologies and control strategies 用于可再生能源集成和储能应用的高效DC-DC变换器：拓扑结构和控制策略综述

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-05-11 DOI: 10.1016/j.conengprac.2025.106371

Mohamed Mezouari, Meriem Megrini, Ahmed Gaga

{"title":"High efficiency DC–DC converter for renewable energy integration and energy storage applications: A review of topologies and control strategies","authors":"Mohamed Mezouari, Meriem Megrini, Ahmed Gaga","doi":"10.1016/j.conengprac.2025.106371","DOIUrl":"10.1016/j.conengprac.2025.106371","url":null,"abstract":"<div><div>The growing demand for efficient energy systems drives the need for advanced power electronics, with DC–DC converters playing a pivotal role in renewable energy integration and energy storage applications. These converters, particularly bidirectional types, are essential for managing the flow of energy in modern power grids and electric vehicle systems. This paper provides a comprehensive review of the latest developments in DC–DC converter technologies, focusing on their topologies, control strategies, and applications in renewable energy systems. The study highlights various converter configurations, including non-isolated and isolated topologies, and evaluates state-of-the-art control techniques such as Artificial Intelligence-Based Control, Model Predictive Control (MPC), and Sliding Mode Control (SMC) for optimizing efficiency and reliability. The importance of bidirectional converters in enabling seamless energy flow for smart grids and energy storage is emphasized, with a particular focus on their role in Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-for-Grid (V4G) systems. Additionally, a detailed analysis of the challenges and opportunities in this field is presented, with identified research gaps paving the way for future advancements in DC–DC converter technologies. This study presents a performance analysis and comparison of control strategies for DC–DC converters, providing an in-depth examination of their impact on the performance of bidirectional DC–DC converters and offering valuable insights for optimizing future energy systems and enhancing the integration of renewable energy sources.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106371"},"PeriodicalIF":5.4,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931399","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