Control Engineering Practice最新文献

英文中文

Motion control strategy for robotic arm using cascaded feature-enhancement ElasticNet broad learning system 使用级联特征增强 ElasticNet 广义学习系统的机械臂运动控制策略

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-15 DOI: 10.1016/j.conengprac.2025.106278

Guoyu Zuo, Shuaifeng Dong, Jiyong Zhou, Shuangyue Yu, Min Zhao

Learning-based control strategies can significantly streamline the process of modeling robotic arms and adjusting control parameters, making them widely used in robotic arm motion control. However, the existing learning-based motion control strategies suffer from insufficient feature extraction, resulting in limited prediction accuracy. To address this problem, this paper proposes a robotic arm motion control strategy based on a cascaded feature-enhanced elastic-net broad learning system (CFE-EN-BLS), which improves the trajectory tracking accuracy of robotic arms. Firstly, a motion control strategy of the cascaded feature-enhanced broad learning system (CFE-BLS) is constructed to fully extract data features to improve joint position-tracking accuracy. Secondly, combined with elastic-net regression, a motion control strategy for the robotic arm based on CFE-EN-BLS is designed to reduce feature redundancy. Finally, the learning parameters of the proposed control strategy are constrained by incorporating Lyapunov theory to bolster the convergence of the control strategy. Simulation and experimental results show that the proposed control strategy can effectively extract data features and achieve high-precision trajectory tracking control of the robotic arm. The position tracking mean-squared-error (MSE) and root-mean-squared-error (RMSE) are 0.00174

r a d

and 0.04167

r a d

, respectively, which represent reductions of 74.71% and 49.76% compared to the existing method.

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引用次数: 0

Active fault-tolerant hybrid control integrated with reinforcement learning application to cable-driven parallel robots 将主动容错混合控制与强化学习集成应用于缆索驱动并联机器人

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-15 DOI: 10.1016/j.conengprac.2025.106277

Yanqi Lu, Weiran Yao

This paper investigates how to maintain control accuracy in cable-driven parallel robots (CDPRs) when faced with actuator faults and lumped uncertainties. An active fault-tolerant hybrid control (AFTHC) scheme integrated with deep reinforcement learning (DRL) is proposed to address the issue. The AFTHC scheme includes a tracking controller, a fixed-time sliding mode observer for fault detection, and a DRL-based fault compensation controller. The fault compensation controller is activated upon detecting an actuator fault to enhance the system stability and recover the control performance. Simulations and experiments are carried out to verify the effectiveness and superiority of the AFTHC scheme. The results indicate that the AFTHC scheme effectively enhances fault tolerance and rapidly recovers control accuracy.

引用次数: 0

Optimizing vehicle handling through Koopman-based model predictive torque vectoring: An experimental investigation

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-15 DOI: 10.1016/j.conengprac.2025.106272

Marko Švec, Šandor Ileš, Jadranko Matuško

This paper presents a Koopman operator model predictive control (KMPC) torque vectoring where the vehicle model is represented by a finite-dimensional approximation of the Koopman operator obtained by using the extended dynamic mode decomposition. The Koopman operator acts like a linear predictor for a nonlinear dynamical system by lifting the nonlinear dynamics into a higher dimensional space where its evolution becomes linear. Different scenarios are simulated using the nonlinear vehicle model to generate the required data set and to obtain the Koopman model used for the KMPC. The KMPC was implemented on the dSPACE MicroLabBox platform, followed by its evaluation in two different experiments. These experiments are conducted using a scaled four-wheel-drive electric vehicle driving on a treadmill that serves as a surrogate for the roadway. The performance of KMPC is compared to that of linear time-varying model predictive controller (LTV-MPC), and nonlinear model predictive controller (NMPC). The results show not only the real-time applicability of KMPC but also a comparable performance and lower computational complexity compared to NMPC. Additionally, an interesting effect of discretization and communication delay on the performance of both LTV-MPC, and NMPC is observed, whereas KMPC demonstrates robustness in this scenario.

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引用次数: 0

Enhancing Multi-operating Modes Knowledge Embedding and Data Augmentation Method for Final Boiling Point Prediction in Hydrogenation Distillation Unit

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-14 DOI: 10.1016/j.conengprac.2025.106273

Mingyu Liang, Yi Zheng, Shaoyuan Li

In process industries, critical quality indicators (CQIs) like diesel Final Boiling Point (FBP) are challenging to monitor online due to equipment limitations, while valuable human expertise remains unformalized for operational guidance. We propose a knowledge-embedded framework integrating three innovations: 1) A modified UMAP optimization injecting human knowledge constraints on data affiliation to align visualization with domain patterns; 2) Production mode identification through labeled operational records, enabling intuitive decision support; 3) Elastic net-based pseudo-mechanistic modeling combined with mode-specific data augmentation for real-time CQI prediction. Experiment was validated the on a hydrogenation distillation unit (HDU). The method proposed in this paper demonstrates excellent performance compared to conventional models (LSTM,SVR,GRU,PSO_MLP) and state-of-the-art approaches (JMSDL), particularly excelling in small dataset scenarios and fluctuating operating modes. The framework systematically solidifies human knowledge into adaptive multi-mode predictions while maintaining low computational complexity for online deployment. The joint optimization of human knowledge and the use of multi-mode approaches enable the application and solidification of human knowledge, embedding it to help improve the prediction of indicators under different conditions.

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引用次数: 0

A scheduling method for blast furnace gas system in steel industry based on a modified generative adversarial network 基于改进生成式对抗网络的钢铁工业高炉煤气系统调度方法

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-14 DOI: 10.1016/j.conengprac.2025.106275

Feng Jin , Canguang Yang , Xiaoxue Wang , Jun Zhao , Wei Wang

Blast furnace gas (BFG) is a crucial secondary energy for the manufacturing process of the steel industry and its efficient utilization is the cornerstone of energy savings and carbon emissions reduction. However, current energy scheduling operation mostly relies on human experience, which is lacking of effectiveness and economy for unknown scenarios (working conditions). In this study, a scheduling method based on a modified generative adversarial network (GAN) is proposed. The state characteristics, which are represented by equal-length information granules, are extracted from the time series of the influenced variables that consisting of a scheduling scenario, and the experience-based scheduling rules are constructed to identify the appropriate scheduling moment. Then, a novel generation framework is built, in which the generator is established by employing multiple GANs to avoid the negative influence of different distribution features on a single discriminator. Finally, a scheduling solution for the corresponding moment is calculated by matching the generated scenarios with the actual one. A series of experiments by using the data coming from a steel enterprise are carried out for verification, and the results show that the scenarios generated via the proposed method are consistent with the actual ones, and the solutions are effective when facing with such kinds of scheduling problems under unknown scenarios.

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引用次数: 0

Numerical research on continuous adjustment and compensation technology under floor cutting trajectory distortion of shearer

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-12 DOI: 10.1016/j.conengprac.2025.106276

Futao Li , Zhongbin Wang , Lei Si , Xiaoyu Zou , Dong Wei , Sen Zhang , Jialiang Dai , Xuesong Wang

Ensuring the flatness of the scraper conveyor is essential for drum height adjustment. However, there have been no studies on drum height adjustment based on floor distortion. Therefore, a continuous adjustment compensation strategy based on floor distortion is proposed. First, the mechanism and influence of floor distortion are analyzed using dynamic simulation software. Subsequently, a mathematical model for the drum height adjustment is developed, and an SMC controller is designed. The response time and tracking capabilities of the system are validated using three typical signals. Finally, a co-simulation platform integrating RecurDyn, AMESim, and Simulink is constructed to enable real-time adjustments of the drum height and traction speed. Simulation results indicate that the maximum absolute error and average absolute error are 6.23 mm and 2.59 mm, respectively, with a velocity of 20 m/min, demonstrating the achievability of the proposed continuous adjustment compensation strategy based on floor distortion.

{"title":"Numerical research on continuous adjustment and compensation technology under floor cutting trajectory distortion of shearer","authors":"Futao Li , Zhongbin Wang , Lei Si , Xiaoyu Zou , Dong Wei , Sen Zhang , Jialiang Dai , Xuesong Wang","doi":"10.1016/j.conengprac.2025.106276","DOIUrl":"10.1016/j.conengprac.2025.106276","url":null,"abstract":"<div><div>Ensuring the flatness of the scraper conveyor is essential for drum height adjustment. However, there have been no studies on drum height adjustment based on floor distortion. Therefore, a continuous adjustment compensation strategy based on floor distortion is proposed. First, the mechanism and influence of floor distortion are analyzed using dynamic simulation software. Subsequently, a mathematical model for the drum height adjustment is developed, and an SMC controller is designed. The response time and tracking capabilities of the system are validated using three typical signals. Finally, a co-simulation platform integrating RecurDyn, AMESim, and Simulink is constructed to enable real-time adjustments of the drum height and traction speed. Simulation results indicate that the maximum absolute error and average absolute error are 6.23 mm and 2.59 mm, respectively, with a velocity of 20 m/min, demonstrating the achievability of the proposed continuous adjustment compensation strategy based on floor distortion.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106276"},"PeriodicalIF":5.4,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386555","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

Reward analysis for participation in ancillary services through coordinated control of EVs and distributed EMSs

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-11 DOI: 10.1016/j.conengprac.2025.106245

Yusuke Muramatsu , Sinkichi Inagaki , Takuma Yamaguchi , Takumi Shibuya , Kenji Hirata , Akira Ito , Tatsuya Suzuki

This paper proposes a method for a community consisting of energy management systems (EMSs) that own electric vehicles (EVs) to participate in the frequency regulation market for ancillary services via an aggregator. The process comprises Problem A: calculating a 24-hour profile of the community’s bidding capacity, and Problem B: tracking control of charge/discharge for EVs parked in each EMS according to regulatory signals transmitted by the transmission system operator (TSO). Each problem is formulated in MIQP and is proven to be equivalent to QP under certain conditions. Furthermore, each EMS’s reward for participating in ancillary services is derived from the relaxed Lagrangian of Problem B. Based on this reward, a strategy is proposed for determining the binding price and whether to participate in the auction, based on the expected state of supply and demand in the power grid. Finally, the simulation results show the rewards and calculation times for each EMS, demonstrating the usefulness of the bidding price strategy.

{"title":"Reward analysis for participation in ancillary services through coordinated control of EVs and distributed EMSs","authors":"Yusuke Muramatsu , Sinkichi Inagaki , Takuma Yamaguchi , Takumi Shibuya , Kenji Hirata , Akira Ito , Tatsuya Suzuki","doi":"10.1016/j.conengprac.2025.106245","DOIUrl":"10.1016/j.conengprac.2025.106245","url":null,"abstract":"<div><div>This paper proposes a method for a community consisting of energy management systems (EMSs) that own electric vehicles (EVs) to participate in the frequency regulation market for ancillary services via an aggregator. The process comprises Problem A: calculating a 24-hour profile of the community’s bidding capacity, and Problem B: tracking control of charge/discharge for EVs parked in each EMS according to regulatory signals transmitted by the transmission system operator (TSO). Each problem is formulated in MIQP and is proven to be equivalent to QP under certain conditions. Furthermore, each EMS’s reward for participating in ancillary services is derived from the relaxed Lagrangian of Problem B. Based on this reward, a strategy is proposed for determining the binding price and whether to participate in the auction, based on the expected state of supply and demand in the power grid. Finally, the simulation results show the rewards and calculation times for each EMS, demonstrating the usefulness of the bidding price strategy.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106245"},"PeriodicalIF":5.4,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust adaptive predefined time prescribed performance attitude control for spacecraft

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-07 DOI: 10.1016/j.conengprac.2025.106271

Srianish Vutukuri, Radhakant Padhi

This article presents a robust adaptive control approach for achieving high-precision attitude control in spacecraft pointing applications. The proposed strategy ensures reference attitude tracking within a predefined time, despite initial state variation and practical challenges such as parametric uncertainties, unknown disturbances, time-varying inertia, actuator saturation, and faults. Additionally, the attitude pointing errors are guaranteed to meet prescribed performance bounds in both transient and steady-state accuracy. This is achieved by constraining the pointing errors to follow a novel predefined time prescribed performance function (PT-PPF), designed in advance to satisfy pointing requirements. The time-varying attitude constraints are enforced using a barrier Lyapunov function (BLF)-based control law, synthesized through the backstepping and dynamic surface control technique. Stability of the proposed controller is rigorously analyzed using Lyapunov theory. The effectiveness of the control law is demonstrated in a high-precision Sun-pointing scenario for a spacecraft in a Sun–Earth

L_{1}

halo orbit, with realistic sensor noise and state feedback provided by an extended Kalman filter.

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引用次数: 0

UDA-ROT: A cross-domain fault diagnosis method for large-scale systems

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-07 DOI: 10.1016/j.conengprac.2025.106268

Shuxuan Zeng , Xin Cheng , Shuai Tan , Xiayi Xu , Qingchao Jiang , Kang Li

Large-scale process industries frequently operate under multiple working conditions. These conditions share similar process technologies, operational principles, and failure mechanisms. Fault diagnosis for different working conditions can Fault diagnosis across these different conditions can be achieved by using programs with a unified label space for both source and target domains. Universal Domain Adaptation based on Reweighted Optimal Transport (UDA-ROT) is proposed for cross-domain fault diagnosis tasks. Firstly, the optimal transport theory is employed to characterize the differences between the source and target domains, in order to identify the unknown classes of the target domain and the private classes of the source domain. The inter-domain adaptation of public classes is achieved through a domain adversarial network. Secondly, a reweighting mechanism is devised relying on the domain adversarial output, in order to refine the optimal transport cost matrix and ensure more precise transport alignment. Finally, the global and local features of the target domain are fully explored to learn the optimal transport problem from the target samples to their prototypes, in order to encourage interclass separability and intraclass consistency of the target clusters. The proposed method provides an effective solution for large-scale systems fault diagnosis.

{"title":"UDA-ROT: A cross-domain fault diagnosis method for large-scale systems","authors":"Shuxuan Zeng , Xin Cheng , Shuai Tan , Xiayi Xu , Qingchao Jiang , Kang Li","doi":"10.1016/j.conengprac.2025.106268","DOIUrl":"10.1016/j.conengprac.2025.106268","url":null,"abstract":"<div><div>Large-scale process industries frequently operate under multiple working conditions. These conditions share similar process technologies, operational principles, and failure mechanisms. Fault diagnosis for different working conditions can Fault diagnosis across these different conditions can be achieved by using programs with a unified label space for both source and target domains. Universal Domain Adaptation based on Reweighted Optimal Transport (UDA-ROT) is proposed for cross-domain fault diagnosis tasks. Firstly, the optimal transport theory is employed to characterize the differences between the source and target domains, in order to identify the unknown classes of the target domain and the private classes of the source domain. The inter-domain adaptation of public classes is achieved through a domain adversarial network. Secondly, a reweighting mechanism is devised relying on the domain adversarial output, in order to refine the optimal transport cost matrix and ensure more precise transport alignment. Finally, the global and local features of the target domain are fully explored to learn the optimal transport problem from the target samples to their prototypes, in order to encourage interclass separability and intraclass consistency of the target clusters. The proposed method provides an effective solution for large-scale systems fault diagnosis.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"157 ","pages":"Article 106268"},"PeriodicalIF":5.4,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349404","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

Continuous Control-Set Model-Predictive Control with stability guarantee for the PWM-VSC

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2025-02-05 DOI: 10.1016/j.conengprac.2025.106246

Juan-Camilo Oyuela-Ocampo , Alejandro Garcés-Ruiz , Santiago Sanchez-Acevedo , Kjell Ljøkelsøy , Salvatore D’Arco

The presence of power electronics converters has become more and more dominant in power systems and this is posing stricter requirements for their controls in terms of stability and performance. The class of Model Predictive Controls (MPC) is particularly well suited for power electronics converters for its inherent ability to incorporate constraints while ensuring high dynamic performance. However, conventional approaches to guarantee stability may complicate the optimal control problem to the extent of making it unrealizable. This paper presents a Continuous Control-Set Model Predictive Control (CCS-MPC) for the Pulse-Width Modulated Voltage Source Converters (PWM-VSC). The bilinear structure of the discrete-time dynamic model is used to obtain a convex optimization problem that ensures a unique and global optimum solution in each step. Moreover, the stability is guaranteed via a discrete-time Lyapunov function derived directly from the Karush–Kuhn–Tucker (KKT) conditions. The proposed control shows a simple implementation with remarkable stability, performance, and clear advantages over the conventional design approach. These properties have been validated both in numerical simulations and experimentally on a 60 kVA converter.

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