Javier Moreno-Valenzuela , Gabriela Zepeda , Raúl Rascón , Marco Moran-Armenta , Jerónimo Moyrón
{"title":"An SLF approach to trajectory tracking control of input-restricted robot manipulators","authors":"Javier Moreno-Valenzuela , Gabriela Zepeda , Raúl Rascón , Marco Moran-Armenta , Jerónimo Moyrón","doi":"10.1016/j.conengprac.2025.106533","DOIUrl":"10.1016/j.conengprac.2025.106533","url":null,"abstract":"<div><div>In this paper, the problem of trajectory tracking of robot manipulators that have input restrictions is addressed. The model adopted for the input nonlinearity is the hard saturation function. An unconstrained nonlinear trajectory tracking controller is introduced, which guarantees trajectory tracking even in the presence of input nonlinearities in the robot manipulator. This approach differs from many other studies, where controllers are limited by the use of smooth saturation functions. In this research, the closed-loop system is analyzed using a strict Lyapunov function (SLF) that allows concluding global uniform asymptotic stability for unperturbed robot manipulators, as well as input-to-state stability (ISS) and global uniform ultimate boundedness (GUUB) of the error signals for the perturbed case. In fact, this paper provides for the first time an SLF-based solution to the problem of designing a trajectory tracking controller for hard-saturation input constrained robot manipulators. Experimental results on a three-degree-of-freedom robot manipulator support the main theoretical findings given in this paper. A comparison with respect to other controllers based on smooth saturation functions is presented. Better tracking accuracy is obtained with the proposed controller.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106533"},"PeriodicalIF":4.6,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922982","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}
Guilherme V. Hollweg , Robert U.M. Viaro , Everson Mattos , Ricardo C.L.F. Oliveira , Humberto Pinheiro , Vinícius F. Montagner
{"title":"Progressively improved LMIs for achieving high-performance robust control of DC–DC converters with low-cost microcontrollers","authors":"Guilherme V. Hollweg , Robert U.M. Viaro , Everson Mattos , Ricardo C.L.F. Oliveira , Humberto Pinheiro , Vinícius F. Montagner","doi":"10.1016/j.conengprac.2025.106502","DOIUrl":"10.1016/j.conengprac.2025.106502","url":null,"abstract":"<div><div>Linear matrix inequalities are recognized by the control community as powerful tools for robust control design. However, its full potential for ensuring high performance and robustness in experimental applications – particularly in DC–DC converters – remains underexplored. The present work aims to investigate progressively improved linear matrix inequalities for designing robust controllers for output voltage regulation in DC–DC buck converters subject to interval parametric uncertainties. The proposed robust controller is developed in the discrete-time domain, considering delay and a polytopic model for the parametric uncertainties, along with constraints on closed-loop poles and in the control gains norm. This results in a strategy capable of achieving high performance in practice, and with a theoretical certification of robust stability based on Lyapunov functions. The proposal is experimentally validated on a physical prototype of a DC–DC buck converter with a low-cost microcontroller, demonstrating superior performance when compared to both a linear quadratic regulator and a state feedback controller optimized through metaheuristics. Finally, the elimination of a current sensor, via a state observer, is proposed, demonstrating robust stability and performance of the augmented system under uncertain and time-varying parameters.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106502"},"PeriodicalIF":4.6,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144918004","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}
{"title":"Robust trajectory tracking and fault-tolerant control for hyperbaric oxygen chambers based on High-order Fully Actuated System approaches","authors":"Nan Zhang, Qijing Lin, Zhuangde Jiang","doi":"10.1016/j.conengprac.2025.106554","DOIUrl":"10.1016/j.conengprac.2025.106554","url":null,"abstract":"<div><div>Precise and reliable control of hyperbaric oxygen chambers (HBOCs) is crucial for effective therapy, yet conventional control algorithms often struggle with limited accuracy, poor disturbance rejection, and inadequate fault handling. To overcome these limitations, this paper presents a novel high-order fully actuated (HOFA) control framework that achieves both high-precision trajectory tracking and fault-tolerant operation in HBOCs. Specifically, a robust trajectory tracking controller is developed that incorporates an extended state observer, model approximations, and a disturbance compensation mechanism to effectively manage nonlinear system dynamics, parameter uncertainties, and actuator saturation. Additionally, a comprehensive fault-tolerant control strategy is introduced, employing fault detection and estimation combined with pole-placement control and redundant control allocation to ensure reliable system performance under various failure scenarios. Experimental results demonstrate that the proposed HOFA-based trajectory tracking and fault-tolerant control scheme significantly outperforms previous HBOC controllers with improved stability and robustness.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106554"},"PeriodicalIF":4.6,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144918003","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}
Kai Sun, Dongzhe Yang, Kaihong Jia, Fangfang Zhang
{"title":"A semi-supervised stochastic configuration network with ordered incremental self-training and pseudo-label confidence evaluation for industrial soft sensor","authors":"Kai Sun, Dongzhe Yang, Kaihong Jia, Fangfang Zhang","doi":"10.1016/j.conengprac.2025.106552","DOIUrl":"10.1016/j.conengprac.2025.106552","url":null,"abstract":"<div><div>Modern industrial processes are characterized by nonlinearity, multiple variables, and a scarcity of labeled data, posing significant challenges for accurate modeling of key performance indicators. To address these difficulties, a novel incremental self-training algorithm is proposed to efficiently leverage unlabeled data for semi-supervised learning of stochastic configuration network (SCN)-based soft sensors. Firstly, a weighted Gaussian mixture model clustering method is developed to rank unlabeled samples. These samples are then sequentially labeled according to their proximity to existing labeled samples in the feature space, thereby lowering the likelihood of inaccurate labeling in early training stages. Secondly, a pseudo-label confidence evaluation algorithm is proposed to quantify the reliability of pseudo-labels, enabling selective inclusion of high-confidence samples into the augmented training dataset. Finally, a semi-supervised learning framework is introduced by integrating the unlabeled sample ranking and the pseudo-label confidence evaluation into the iterative self-training process of SCN. This approach augments the training dataset through ordered and quality-controlled increments to enhance model performance. Experimental validation on both a public case and an actual industrial case demonstrates that the proposed algorithm outperforms existing state-of-the-art methods. In the industrial case, our approach reduced the mean absolute error by 26.3% and 25.0%, the mean squared error by 14.5% and 14.6%, while improving the correlation coefficient by 9.9% and 9.1%, compared to the state-of-the-art self-training and generative model methods, respectively. Additionally, ablation studies are conducted to evaluate the contribution of different techniques on the model performance.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106552"},"PeriodicalIF":4.6,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913016","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}
Jingwu Chen , Wei Pan , Tao Cao , Zhouyuan Qian , Lin Zhang , Xinbo Chen , Hong Chen
{"title":"Auxiliary-enhanced neural networks for electric vehicle dynamics: Advancing tire force and state estimation during wheel slip","authors":"Jingwu Chen , Wei Pan , Tao Cao , Zhouyuan Qian , Lin Zhang , Xinbo Chen , Hong Chen","doi":"10.1016/j.conengprac.2025.106550","DOIUrl":"10.1016/j.conengprac.2025.106550","url":null,"abstract":"<div><div>Accurately perceiving vehicle states and tire forces is crucial for the advanced safety and control technologies in vehicles. However, due to the highly complex and nonlinear characteristics of both vehicles and tires, extracting these states remains a significant challenge. This paper introduces a novel approach that combines Long Short-Term Memory (LSTM) neural networks with vehicle dynamics to address these challenges. Using real vehicle data, the study develops an attention-enhanced LSTM network to estimate tire forces. The architecture incorporates an attention mechanism (AM) to strengthen relevant feature extraction, with Bayesian optimization employed for hyperparameter tuning to effectively map sensor signals to tire forces. . A decoupled dual Unscented Kalman Filter (UKF) is also employed to estimate lateral and longitudinal velocities. It incorporates normalized tire forces, estimated by a neural network, as observations to enhance the convergence and accuracy of the UKF, providing a comprehensive vehicle velocity estimate. Finally, the performance of the algorithm was validated through DLC and slalom experiments. Under these conditions, the proposed method reduced the RMSE of the estimated longitudinal and lateral tire forces by up to 60.63% and 44.26%, respectively, compared to other methods. Additionally, RMSE of the estimated longitudinal and lateral velocity decreased by 41.31%, 50.46%, 0.97%, and 59.22%, respectively.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106550"},"PeriodicalIF":4.6,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903814","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}
Yuanqiao Fan , Xiaolong Deng , Xixiang Yang , Xiaoqun Cao , Fangchao Bai , Yuan Long , Minyu Liu
{"title":"Coverage control with global connectivity maintenance for multiple stratospheric airships","authors":"Yuanqiao Fan , Xiaolong Deng , Xixiang Yang , Xiaoqun Cao , Fangchao Bai , Yuan Long , Minyu Liu","doi":"10.1016/j.conengprac.2025.106544","DOIUrl":"10.1016/j.conengprac.2025.106544","url":null,"abstract":"<div><div>Stratospheric airships offer flexible and extensive coverage for the communication service and earth observation when deployed in formations. However, limited communication ranges may lead to network disconnection during dispersed movements. This paper presents a hierarchical guidance algorithm addressing coverage deployment, connectivity maintenance, and windward station-keeping for multiple stratospheric airships. The proposed guidance modifies nominal deployed positions, making it well-suited for underactuated systems and station-keeping scenarios. A novel discrete distributed estimator is introduced to evaluate algebraic connectivity. Furthermore, a motion control strategy based on Control Barrier Functions is developed for precise longitudinal velocity and yaw control under thrust limitation. Extensive simulations validate the framework’s effectiveness in maintaining connectivity near a predefined threshold, optimizing coverage, and ensuring stable formation behavior. The approach outperforms the baselines and demonstrates strong potential for broader application to underactuated platforms such as unmanned surface vehicles and autonomous ground vehicles, which face similar constraints and environmental disturbances.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106544"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895437","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}
Wei Fan , Yanlong Ji , Huabing Wen , Xin Liu , Haiquan Yu , Cong Yu , Qingdong Meng
{"title":"Concurrent quality and process monitoring with a probabilistic sparse nonlinear dynamic method","authors":"Wei Fan , Yanlong Ji , Huabing Wen , Xin Liu , Haiquan Yu , Cong Yu , Qingdong Meng","doi":"10.1016/j.conengprac.2025.106551","DOIUrl":"10.1016/j.conengprac.2025.106551","url":null,"abstract":"<div><div>In industrial processes, significant attention has been directed toward developing monitoring frameworks that effectively capture the interactions between process variables and quality-related variables. This paper presents a novel probabilistic sparse nonlinear dynamic method, CPSINDy, for concurrent quality and process monitoring in industrial systems. The proposed method incorporates nonlinear dynamics by formulating a comprehensive framework based on a probabilistic state–space model. Subsequently, leveraging the particle filtering technique, parameter estimation is performed using the Expectation–Maximization algorithm. After that, four dynamic indices are introduced to detect abnormal operating conditions. Both feasibility and superiority of the presented model are confirmed through three realistic industrial fault cases. Results demonstrate that CPSINDy based model outperforms traditional approaches in terms of fault detection rates and false alarm rates.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106551"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894501","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}
M. Niederer , P. Zeman , S. Sannes , H. Seyrkammer , G. Helekal , A. Kugi , A. Steinboeck
{"title":"Nonlinear model predictive temperature control of a cooling process for steel strips undergoing phase transformations","authors":"M. Niederer , P. Zeman , S. Sannes , H. Seyrkammer , G. Helekal , A. Kugi , A. Steinboeck","doi":"10.1016/j.conengprac.2025.106512","DOIUrl":"10.1016/j.conengprac.2025.106512","url":null,"abstract":"<div><div>The cooling of hot steel causes phase transformations that are directly influencing the material properties. Precise temperature control is therefore essential for producing high-quality steel products. The paper proposes a nonlinear model predictive controller for accurate tracking control of the strip temperature in a cooling section of a continuous steel strip processing line of voestalpine Stahl GmbH. The controller is based on a dynamic model of the local temperature and phases of the strip material. The controller computes optimal trajectories of the system inputs so that the strip reaches a strip-specific target temperature. A tailored constrained nonlinear dynamic optimization problem is numerically solved in the control algorithm using the Levenberg–Marquardt method. The gradient and the approximate Hessian of the objective function are analytically computed using an adjoint-based approach. Measurements at the real processing line demonstrate the excellent control performance. Long-term analysis shows that the model predictive controller improves both the accuracy and the homogeneity of the strip temperature compared to the previously used PI-control scheme. On average, the reduction of the mean temperature error is 51%, and the improvement of the temperature homogeneity is 25%.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106512"},"PeriodicalIF":4.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894500","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}
{"title":"A real-time scheduling approach for two-cluster tools with wafer revisiting","authors":"Genghong Wang , Naiqi Wu , Yan Qiao","doi":"10.1016/j.conengprac.2025.106547","DOIUrl":"10.1016/j.conengprac.2025.106547","url":null,"abstract":"<div><div>In semiconductor manufacturing, there are revisiting processes where some processing steps are required to be visited by a wafer for multiple times. In many cases, the production of such revisiting processes is implemented in a multi-cluster tool composed of multiple individual cluster tools. Due to the complex wafer flow patterns and the coordination requirement of multiple robots, it is very challenging to schedule such a tool and there is no research report on this issue. This work deals with the scheduling problem of a two-cluster tool with wafer revisiting. To cope with the huge system state space, a simulation-based method is proposed. Based on this method, a real-time scheduling approach is proposed to efficiently find a good feasible solution. To implement the system simulation, a simulation model is developed based on object-oriented programming, and it can describe various wafer flow patterns and varied tool configurations. Furthermore, in this way, a schedule by optimally configuring process modules (PMs) for the operations can be efficiently found. Experiments are presented to demonstrate the proposed approach.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106547"},"PeriodicalIF":4.6,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893814","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}
Liqiang Jin , Neng Qiu , Duanyang Tian , Qixiang Zhang , Fei Teng , Bohao Jin , Feng Xiao
{"title":"MPC-based path tracking strategy for 4WID&4WIS vehicles using B-spline approximation and state-dependent reference","authors":"Liqiang Jin , Neng Qiu , Duanyang Tian , Qixiang Zhang , Fei Teng , Bohao Jin , Feng Xiao","doi":"10.1016/j.conengprac.2025.106546","DOIUrl":"10.1016/j.conengprac.2025.106546","url":null,"abstract":"<div><div>Four-wheel independent drive and steering (4WID&4WIS) vehicles offer great potential for improving path tracking accuracy and vehicle stability. To fully leverage these capabilities, model predictive control (MPC) is widely adopted as an advanced path tracking strategy. However, conventional MPC approaches often struggle to simultaneously achieve high tracking accuracy and computational efficiency due to the trade-off between control horizon length and real-time feasibility. Furthermore, time-varying reference outputs can degrade tracking performance and even threaten vehicle stability, particularly when the vehicle deviates from predetermined temporal constraints. To address these challenges, this paper proposes an enhanced MPC strategy based on B-spline approximation and state-dependent reference (BS-MPC). Specifically, the control input sequence is approximated by a quasi-uniform B-spline curve, which significantly reduces the number of optimization variables and improves computational efficiency. Simultaneously, the reference output is adaptively generated as a function of the predicted vehicle state, which naturally couples longitudinal, lateral, and yaw motions and better aligns with the fundamental objectives of tracking control. Comprehensive Monte Carlo simulations validate the robustness and practical stability of the proposed BS-MPC controller under realistic uncertainty conditions. Finally, hardware-in-the-loop simulations and full-scale vehicle experiments demonstrate that, compared to conventional MPC, the proposed method reduces the maximum tracking errors by 86.2% under normal conditions and by 96.8% under extreme conditions.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"165 ","pages":"Article 106546"},"PeriodicalIF":4.6,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895436","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}