Chengxiang Liu , Yehui Li , Zhiwei Cui , Heng Zhang , Yichong Sun , Zheng Li
{"title":"Robust adaptive dynamic control of electromagnetically actuated soft-tethered robots for medical intervention","authors":"Chengxiang Liu , Yehui Li , Zhiwei Cui , Heng Zhang , Yichong Sun , Zheng Li","doi":"10.1016/j.conengprac.2024.106107","DOIUrl":"10.1016/j.conengprac.2024.106107","url":null,"abstract":"<div><div>Electromagnetically actuated soft-tethered robots (EASTRs) exhibit significant potential for medical intervention applications due to their compact size and minimal invasiveness. However, their inherent nonlinear behavior and susceptibility to unexpected disturbances present challenges for achieving robust control performance. To address this issue, in this paper, a dynamic model for EASTRs is first established, which encompasses the actuation model of the magnetic tip and the dynamic model of the soft tether. Subsequently, a robust adaptive dynamic controller is designed to compensate for the inaccuracy of the established dynamic model, thus ensuring robust control performance. The proposed approach integrates adaptive laws based on the Lyapunov method to effectively handle time-varying parameters and disturbances. Experimental results present an excellent control accuracy of the proposed scheme in trajectory tracking tasks, showcasing its superior performance compared to passive schemes and classical proportional–derivative control. This research contributes valuable insights into advancing the control capabilities of EASTRs for diverse applications in medical practices.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106107"},"PeriodicalIF":5.4,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423364","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":"On the selection of control structures using process operability analysis","authors":"Victor Alves, Fernando V. Lima","doi":"10.1016/j.conengprac.2024.106117","DOIUrl":"10.1016/j.conengprac.2024.106117","url":null,"abstract":"<div><div>This work aims to develop a generalizable framework for control structure selection using process operability analysis. Current approaches for selecting controlled variables in chemical processes are limited to assessing system attributes individually, focusing on controller performance or the economic impact based on a constant setpoint policy. However, the competitive industrial manufacturing market requires a holistic approach for control structure selection in large-scale plants that takes into account multiple factors. In particular, process operability can help to enable a generalizable approach that is able to select control structures that are operable considering economic and performance factors simultaneously. To achieve this goal, a framework that uses the Operability Index (OI) as a metric for ranking the achievability of the control objectives for the selected control structures is developed. To test the framework, a depropanizer distillation column is investigated as a case study associated with large-scale energy systems. This work thus introduces novel formulations and algorithms for the control structure selection problem, enhancing the design, operations, and synthesis of existing and future industrial systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106117"},"PeriodicalIF":5.4,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423370","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 adaptive PID control of functional electrical stimulation for drop-foot correction","authors":"Ghazal Tanhaei , Hamed Habibi , William Holderbaum , Noureddin Nakhostin Ansari","doi":"10.1016/j.conengprac.2024.106090","DOIUrl":"10.1016/j.conengprac.2024.106090","url":null,"abstract":"<div><div>A robust, adaptive proportional–integral–derivative (PID) control strategy is presented for controlling ankle movement using a functional electrical stimulation (FES) neuroprosthesis. The presented control strategy leverages the structurally simple PID controller. Moreover, the proposed PID controller automatically tunes its gains without requiring prior knowledge of the musculoskeletal system. Thus, in contrast to previously proposed control strategies for FES, the proposed controller does not necessitate time-consuming model identification for each patient. Additionally, the computational cost of the controller is minimized by linking the PID gains and updating only the common gain. As a result, a model-free, structurally simple, and computationally inexpensive controller is achieved, making it suitable for wearable FES-based neuroprostheses. A Lyapunov stability analysis proves uniformly ultimately bounded (UUB) tracking of the joint angle. Results from the simulated and experimental trials indicate that the proposed PID controller demonstrates high tracking accuracy and fast convergence.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106090"},"PeriodicalIF":5.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423362","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}
Dong Wei , Houzhe Wang , Xia Liu , Xin Li , Jinheng Gu , Xiaoyu Zou , Chao Tan , Lei Si
{"title":"Adaptive tracking control method for shearer cutting trajectory based on the combined strategy","authors":"Dong Wei , Houzhe Wang , Xia Liu , Xin Li , Jinheng Gu , Xiaoyu Zou , Chao Tan , Lei Si","doi":"10.1016/j.conengprac.2024.106116","DOIUrl":"10.1016/j.conengprac.2024.106116","url":null,"abstract":"<div><div>Adaptive tracking control method for shearer remains challenging caused by the contradiction between coal recovery rate and equipment safety under current technological limitations, has drawn more and more attention over the past decades due to its important role in reducing personnel, increasing safety, and improving efficiency for underground mining. Therefore, a novel adaptive tracking control method for shearer cutting trajectory based on the combined strategy is proposed, whose core is the switching method of the sub-strategies based on the linear quadratic regulator (LQR) and error band control (EBC) with switching threshold determined by the Multi-strategy Marine Predator Algorithm. The performance of the proposed method is demonstrated by comparing with the existing methods reported. The experimental results reveal that the proposed method maintains a high recovery rate while improving coal mining efficiency.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106116"},"PeriodicalIF":5.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423363","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}
Biao Lu , Haixin Cao , Yongchun Fang , Jing Zhang , Yunsong Hao
{"title":"Robust motion control for an underactuated wheeled bipedal robot utilizing sliding mode strategy","authors":"Biao Lu , Haixin Cao , Yongchun Fang , Jing Zhang , Yunsong Hao","doi":"10.1016/j.conengprac.2024.106108","DOIUrl":"10.1016/j.conengprac.2024.106108","url":null,"abstract":"<div><div>In recent years, wheeled bipedal robots (WBRs) have become one of the frontier fields of robotic research, attracting immense interest from scholars globally. They can not only move rapidly on flat ground through wheels but also possess satisfactory adaptability to uneven terrain due to the introduction of legs. With concise structure and strong agility, WBRs have broad prospects of application in logistics, routing inspection, home service, and so on. However, the inherent underactuation of such robots presents a significant challenge in terms of balance control, particularly in the face of uncertainties and external disturbances. To address this problem, this paper presents a sliding mode control strategy for WBRs, which guarantees robust balance performance even under the influence of various external disturbances. Specifically, the dynamic equations of WBRs are first rearranged in cascaded form, facilitating targeted control design. After that, the wheel torque and leg supporting force are carefully devised to ensure that the sliding surfaces converge to zero within a fixed time. Rigorous Lyapunov-based analysis has shown that the desired equilibrium point is asymptotically stable. Finally, extensive hardware experiments are undertaken, providing convincing evidence of the superior balance control performance achieved by the proposed method.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106108"},"PeriodicalIF":5.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423361","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":"Combined simple adaptive and integral terminal sliding mode control for industrial feed drive systems","authors":"Haryson Johanes Nyobuya , Naoki Uchiyama","doi":"10.1016/j.conengprac.2024.106109","DOIUrl":"10.1016/j.conengprac.2024.106109","url":null,"abstract":"<div><div>In the manufacturing industry, feed drive systems are utilized for various applications in industrial machines. These systems are crucial components for ensuring precision in motion control and are, therefore, expected to offer high tracking performance. This study focuses on application of integral terminal sliding mode control (ITSMC) to a feed drive system because of its robustness against disturbances and convergence of the tracking error in finite-time. However, its design requires plant dynamics model. To alleviate this concern, a solution of modifying the original ITSMC law to adaptive ITSMC law based on simple adaptive control (SAC) technique is used. To implement SAC-like adaptive law to a real plant, a property of “almost strictly positive real (ASPR)” is required to be satisfied. ASPR property is satisfied using velocity-based augmented output signal that ensures the stability. In experimental results, the adaptive controller follows the reference trajectory more precisely than conventional methods.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106109"},"PeriodicalIF":5.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423410","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":"Multi-phase weighted stator current tracking using a hyper-plane partition of the control set","authors":"M.R. Arahal , M.G. Satué , F. Barrero","doi":"10.1016/j.conengprac.2024.106114","DOIUrl":"10.1016/j.conengprac.2024.106114","url":null,"abstract":"<div><div>This paper presents a new optimization technique for Finite Control Set Model Predictive Control (FCS-MPC) of multi-phase induction machines. The proposal allows for a fast computation of the control signal while simultaneously considering stator currents in the <span><math><mrow><mi>α</mi><mo>−</mo><mi>β</mi></mrow></math></span> (torque producing) plane and the <span><math><mrow><mi>x</mi><mo>−</mo><mi>y</mi></mrow></math></span> (harmonics) plane. The combinatorial search of the optimization phase is eliminated. Also, unlike previous approaches, the proposed region identification algorithm can be utilized in conjunction with weighting factors in the cost function. The optimization is done using a hyper-plane partition of the control set. The partition provides the weighted FCS-MPC solution with significantly less computation needs allowing for shorter sampling periods. The method is tested experimentally in a 5-phase induction motor showing enhanced results.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106114"},"PeriodicalIF":5.4,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423409","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":"Fuzzy adaptive impedance control for the two-layered vertical cable-driven parallel robot","authors":"Thanh-Hai Nguyen , Kwan-Woong Gwak","doi":"10.1016/j.conengprac.2024.106110","DOIUrl":"10.1016/j.conengprac.2024.106110","url":null,"abstract":"<div><div>This study unveils a novel two-layered vertical octahedron cable-driven parallel robot (TLVO CDPR), distinctively engineered for effective force interactions with vertical surfaces while preventing collision with cables. It pioneers an innovative control strategy integrating a position-based fuzzy adaptive impedance controller with a fuzzy Proportional – Integral – Derivative (PID) controller, adeptly managing both the pose and contact force of the robot. While dual control application is often found in rigid-link robots, it remains a largely unexplored frontier in the realm of CDPRs, despite its critical importance in sectors like manufacturing and assembly. The fuzzy adaptive mechanism significantly boosts impedance control efficacy in the face of unpredictable, non-uniform working surfaces, ensuring algorithmic stability and convergence. Concurrently, fuzzy logic is harnessed to optimize PID controller performance. The forward kinematics challenge is efficiently tackled using a least squares method coupled with an Inertial Measurement Unit (IMU), ensuring swift and precise solutions. The robustness and adaptability of the robot and its control systems are thoroughly validated through extensive experimental trials, involving diverse trajectories and varying uncertainties on vertical working surfaces.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106110"},"PeriodicalIF":5.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423407","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":"Selection of alarm deadbands and delay timers with their connections based on risk indicators for removing nuisance alarms","authors":"Zheng Zhang, Jiandong Wang, Yan Qi","doi":"10.1016/j.conengprac.2024.106113","DOIUrl":"10.1016/j.conengprac.2024.106113","url":null,"abstract":"<div><div>Alarm systems are crucial to the safety and efficiency of industrial processes, but they may be contaminated by massive nuisance alarms. Alarm deadbands and delay timers with their connections are often used to remove nuisance alarms. However, different process variables are with different characteristics of alarm events, so that it is necessary to determine which one of these alarm systems is the most appropriate for a given process variable. This paper proposes a method to select the most suitable alarm system for a given process variable, by formulating an indicator to evaluate the risk of missed abnormality detections. The technical challenge is about how to calculate the uncertainty of the risk indicator. The Bayesian estimation approach is utilized to yield confidence intervals of the risk indicator for addressing the technical challenge. The alarm system with the lowest risk indicator is chosen as the most appropriate one. Numerical and industrial examples are presented to support the proposed method.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106113"},"PeriodicalIF":5.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142423408","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}
Xiuli Zhu , Yan Song , Peng Wang , Ling Li , Zixuan Fu
{"title":"Data-driven adaptive and stable feature selection method for large-scale industrial systems","authors":"Xiuli Zhu , Yan Song , Peng Wang , Ling Li , Zixuan Fu","doi":"10.1016/j.conengprac.2024.106097","DOIUrl":"10.1016/j.conengprac.2024.106097","url":null,"abstract":"<div><div>Data-driven modeling is a crucial technology for the real-time monitoring of large-scale industrial systems. However, it often suffers from the redundancy of input variables, resulting in low prediction and modeling accuracy. To address this issue, a novel feature selection method, namely adaptive and stable feature selection based on a reference vector-guided evolutionary multi-objective optimization algorithm (ASFS-RVEA), is proposed in this paper. The proposed ASFS-RVEA comprehensively considers four important objectives: the number of features, prediction accuracy, the dissimilarity of selected features, and the mitigation of feature redundancy.Considering the interaction and conflict among these four objectives, a multi-objective optimization problem with an unknown Pareto front is formulated to find an optimal balance among them, thereby obtaining promising and convincing results. Furthermore, Jensen–shannon divergence (JSD) is introduced to the RreliefF algorithm to account for the data distribution information between various input features and key output variables, guiding population crossover and mutation. This greatly enhances the robustness of the algorithm when handling data with different distributions. Next, a reference vector adapting strategy is proposed to update the generation based on dynamically changing distributions, which helps accelerate convergence in the optimization process. Finally, experiments conducted on datasets collected from the Dow process and the polyester polymerization process demonstrate the effectiveness of the proposed ASFS-RVEA.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"153 ","pages":"Article 106097"},"PeriodicalIF":5.4,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326367","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}