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A hierarchical, enhanced information structure-based fault-tolerant control scheme for industrial interconnected systems with directed acyclic topology Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-11 Jingjing Gao, Xu Yang, Jian Huang, Qing Li, Xian Zhou, Jiarui Cui
This paper is concentrated on the analysis and design scheme of enhanced information structure-based fault-tolerant control for industrial interconnected systems with directed acyclic topology. To this end, the extended state-space expressions of the subsystems are first derived, where the unknown state values of the subsystems are represented by available process input/output data. Then, the direct
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Linear unknown input-state observer for nonlinear dynamic models Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-10 Salvatore Pedone, Adriano Fagiolini
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Nonlinear model predictive control of chiller plant demand response with Koopman bilinear model and Krylov-subspace model reduction Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-09 Chao Pan, Yaoyu Li
The demand response (DR) operation of chiller plants has been approached with model predictive control (MPC) strategies, based on day-ahead electricity price, knowledge of upcoming weather and load profiles. Since chiller plants feature significant nonlinearities across wide variations in ambient and load conditions, nonlinear MPC (NMPC) is the typical alternative to piecewise linear MPC design, however
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Distributed data-driven voltage control for active distribution networks with changing grid topologies Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-09 Wenjie Xiong, Zhiyuan Tang, Xinyu Cui
In this paper, a novel distributed data-driven voltage control approach is proposed to handle unexpected voltage violations in active distribution networks (ADNs) with changing system topologies. In the proposed control scheme, once a voltage violation occurs, the PV inverters and battery energy storage systems will be coordinated to provide voltage corrective control. The whole control scheme is designed
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Model-based velocity-tracking-control of self-erecting industrial tower cranes Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-09 Matthias Thomas, Tobias Englert, Oliver Sawodny
Although crane control has been a research field for decades, active sway damping control for tower cranes is not yet established in industry. For different reasons, the concepts (mainly validated with laboratory cranes) cannot be applied to large-scale tower cranes. In this paper, a model-based control concept under consideration of the elastic deformation of the crane structure is presented and validated
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Model based precise register control method for shaft-driven Roll-to-Roll(R2R) systems Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-08 Tao Zhang, Ying Zheng, Zhihua Chen
Shaft-driven Roll-to-Roll (R2R) printing systems have advantages in keeping the printing rolls synchronously rotating, thereby reducing the register errors of R2R printing systems. However, tension oscillations and propagation are still inevitable due to other factors such as disturbances, which lead to the fluctuation of register errors. In this paper, a new mechanical model is established for the
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Optimal fault-tolerant control with radial force compensation for multiple open-circuit faults in multiphase PMSMs - A comparison of n-phase and multiple three-phase systems Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-08 René Lenz, Andreas Deutschmann-Olek, Andreas Kugi, Wolfgang Kemmetmüller
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Safe motion planner for autonomous driving based on LPV MPC and reachability analysis Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-06 Álvaro Carrizosa-Rendón, Vicenç Puig, Fatiha Nejjari
This article presents an innovative optimization-based solution to the collision avoidance challenge for autonomous vehicles. The presented approach consists in an online motion planner designed to define feasible and efficient paths able to deal with dynamic surroundings while implicitly ensure safety in the proposed maneuvers. The fact of considering moving obstacles inside the motion planner increases
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Fixed-time adaptive neural control of electro-hydraulic system with model uncertainties: Theory and experiments Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-04 Chen Wang, Jianhui Wang, Qing Guo, Xing Ren, Yuancao Cao, Dan Jiang
Nonlinearities, uncertainties and unknown external loads decline tracking dynamic performance and steady-state accuracy of electro-hydraulic systems. Most existing electro-hydraulic controllers have well guaranteed both the cylinder position and the load pressure asymptotic stable or uniformly ultimately bounded. However, the corresponding output response is relatively slow and achieves the desired
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On the robust control design of multiple resonant controllers for the parallel operation of UPSs Control Eng. Pract. (IF 4.9) Pub Date : 2024-04-04 Guilherme Keiel, Jeferson Vieira Flores, Luís Fernando Alves Pereira
This paper presents a methodology for the synthesis of multiple resonant controllers in the voltage regulation loop of uninterruptible power supplies (UPSs) operating in parallel with droop control. The resonant controller gains are calculated through a convex optimization problem aiming to attenuate the rms value of circulating current between the UPSs. Linear matrix inequalities (LMIs) constraints
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Physics-informed data-driven model of dehydration reaction stage in the sintering process of ternary cathode materials Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-30 Lei Xu, Chunhua Yang, Xiaodong Xu, Ning Chen
The sintering process is the main process that affects the performance of ternary cathode materials. Due to the closed, continuous, and long-term characteristics of the sintering process carried out in a roller kiln, the reaction state including reaction degree, particle size, and etc., of the raw materials cannot be directly obtained through sampling detection, resulting in ineffective temperature
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Online adaptive identification of clutch torque transmissibility for the drivability consistency of high-performance production vehicles Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-30 Sooyoung Kim, Heeyun Lee, Jinsung Kim, Giseo Park
Drivability in vehicles with a wet-type dual-clutch transmission (DCT) relies heavily on the precise torque transfer control of the clutch to efficiently distribute the engine torque to the wheels. However, the large variation in the clutch torque transmissibility caused by temperature and wear and the lack of torque sensors for the driveline in production vehicles are the two significant challenges
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A Bayesian network method using transfer learning for solving small data problems in abnormal condition diagnosis of fused magnesia smelting process Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-29 Hao Yan, Xinchun Jia, Kang Li, Fuli Wang
Intelligent abnormal condition diagnosis is key to the safe and stable operation of the fused magnesia smelting process (FMSP). Existing studies have applied the Bayesian network (BN) to the FMSP with sufficient data. However, learning an accurate BN model for a new FMSP using small data isn't easy. Furthermore, the unreasonable diagnosis may seriously affect product quality and security threats. To
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Distributed multi-horizon model predictive control for network of energy hubs Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-27 Varsha N. Behrunani, Hanmin Cai, Philipp Heer, Roy S. Smith, John Lygeros
The increasing penetration of renewable energy resources has transformed the energy system from a traditional hierarchical energy delivery paradigm to a distributed structure. Local energy hubs activates synergies among energy carriers rendering flexibility to the system and gives rise to possible energy trading among networked local energy hubs. Joint operation of such hubs and peer-to-peer trading
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Multi-Source energy optimization method for supersonic aircraft based on multi-objective adaptive covariance matrix and chaotic search group algorithm Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-23 Xingjian Jin, Jingyang Zhang, Fengying Zheng, Zhongze He, Haoliang Zhang, Liang Xu
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Local regularization assisted split augmented Lagrangian shrinkage algorithm for feature selection in condition monitoring Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-22 Yufei Gui, Xiaoquan Tang, Zepeng Liu
Feature selection plays a vital role in improving the efficiency and accuracy of condition monitoring by constructing sparse but effective models. In this study, an advanced feature selection algorithm named the local regularization assisted split augmented Lagrangian shrinkage algorithm (LR-SALSA) is proposed. The feature selection is realized by solving a -norm optimization problem, which usually
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A recommender system for human operators in industrial automation Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-21 Negar Yassaie, Ahmad W. Al-Dabbagh
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Automatic alignment of underwater snake robots operating in wakes of bluff bodies Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-20 Amer Orucevic, Marianna Wrzos-Kaminska, Mads Erlend Bøe Lysø, Kristin Ytterstad Pettersen, Jan Tommy Gravdahl
This paper presents the development of controllers to automatically align an underwater snake robot (USR) with a wake that forms behind a bluff body, while swimming at a desired distance to the object. The low-level controllers stabilize the joint motion of the USR to a swimming gait while achieving a desired orientation and tangential velocity. The high-level controllers are designed to select references
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Signed-data reinforced observer-based fault diagnosis for virtually-coupled electric multiple units trains Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-19 Tao Wen, Shigen Gao, Jincheng Wang, Clive Roberts
Virtual coupling has been recognized as a promising yet challenging technology for the next generation of train control systems. As a mean of guaranteeing the safety of closer-running of virtually-coupled electric multiple units (EMU) trains, fault detection and diagnosis play a critical role in perceiving abnormal running conditions. This paper develops a new signed-data reinforced observer-based
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A machine learning-based motion training approach applied to multilegged and bipedal robots Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-19 Ping-Huan Kuo, Chiou-Jye Huang, Wei-Cyuan Yang, Po-Wei Hsu, Wei-Hsin Chang, Xin-Yu Chen
To promptly gain an understanding of disasters as they occur and to draft plans for search and rescue operations, various types of robots are used. Robots not only increase rescue efficiency but also reduce firefighter casualties. Therefore, this study investigated how bionic robots can be utilized to search destroyed and chaotic disaster sites as quickly as possible. However, manually adjusting the
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Experimental assessment of integral-type terminal sliding mode control designed for a single-phase grid-interlinked PV system Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-19 Khalid Chigane, Mohammed Ouassaid
Due to the increasing global adoption of grid-connected photovoltaic (PV) systems and their unpredictable power production behavior, as well as their interactions with the electrical network, PV system controllability is a major aspect that should be taken into consideration. The paper under discussion implements an integral-type terminal sliding mode control (ITTSMC) technique for a single-stage,
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Iterative real-time optimization of a membrane pilot plant Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-16 Afaq Ahmad, Radoslav Paulen, Richard Valo, Miroslav Fikar, Sebastian Engell
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Cooperative control strategy of trajectory tracking and driving stability for distributed-drive vehicles under extreme conditions Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-16 Fei Teng, Junnian Wang, Liqiang Jin, Zhenyu Wang, Zidong Zhou, Zhe Liu
Active chassis dynamics control has become increasingly important in recent years for achieving high-level automated driving of intelligent electric vehicles. To improve tracking performance of the commonly-used model predictive control (MPC) in extreme scenarios, such as emergency lane changing, an improved MPC motion stability controller (MPC_ISMC) based on sliding mode variable structure active
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Fixed-structure parameter-dependent state feedback controller: A scaled autonomous vehicle path-tracking application Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-15 Ariel M. Borrell, Vicenç Puig, Olivier Sename
This paper introduces theoretical conditions for the computation of a novel type of state-feedback controller that makes use of Linear Parameter Varying approaches for synthesis. The novelty of this new State-Feedback controller lies on the fact that the controller has a fixed structure with constants matrix gains. However, the controller gains are affine on a parameter dependent basis function, which
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Model-free adaptive tensor product control for a class of nonlinear systems Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-14 Dongya Zhao, Shouli Gao, Fei Li, Xinggang Yan, Sarah K. Spurgeon
This paper presents a new data driven control for a class of discrete-time multiple input and multiple output nonlinear systems which uses the principles of model-free adaptive control and the tensor product. The design of a linearization model using the notion of the tensor product overcomes reset problems in the calculation of the pseudo partial derivative and also improves control performance. The
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A pair of two-stage Kalman filters to detect and isolate failures in aircraft with redundant actuators Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-14 Rafael A. Cordeiro, José R. Azinheira, Alexandra Moutinho
As critically-safe systems, aircraft must be able to adapt if a failure occurs. A fast failure detection may reduce the possibility of loss of control in-flight. Model-based Failure Detection and Isolation Systems (FDIS) have been proposed to identify actuation failures in aircraft, being most of them based on Multiple Models approaches. An additional challenge in FDIS strategies for aircraft is the
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Comparative study of maximum power point tracking control for PV arrays system integration process Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-14 Jianwen Meng, Qihao Guo, Meiling Yue, Demba Diallo
Given the stochastic nature of solar energy, integrating PV arrays with energy storage systems (ESSs) is crucial for a consistent power supply. Effective maximum power point tracking (MPPT) control is of great importance in this context. The significance lies not just in achieving high energy efficiency but also in ensuring overall system safety and reliability, as rapid and stable power tracking control
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Learning-based multi-agent MPC for irrigation scheduling Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-12 Bernard T. Agyeman, Mohamed Naouri, Willemijn M. Appels, Jinfeng Liu, Sirish L. Shah
Amid concerns about freshwater scarcity, the agricultural sector faces challenges in water conservation and optimizing crop yields, highlighting the limitations of traditional irrigation scheduling methods. To overcome these challenges, this paper introduces a unified, learning-based predictive irrigation scheduler that integrates machine learning and Model Predictive Control (MPC), while also incorporating
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Force tracking control for hydraulically actuated adaptive high-rise buildings Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-10 Spasena Dakova, Oliver Sawodny, Michael Böhm
Adaptive high-rise buildings comprise sensors, a control unit and actuators and are able to actively compensate disturbances, allowing the realization of significantly lighter structures compared to conventional constructions. This publication presents the development of a force tracking controller for hydraulic actuators on adaptive high-rise buildings. First, nonlinear models of a single- and a double-acting
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Improved nonlinear active disturbance rejection control for a continuous-wave pulse generator with cascaded extended state observer Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-08 Zhidan Yan, Shiyan Deng, Zhenyu Yang, Xudong Zhao, Nan Yang, Yunfeng Lu
The generator rotor is crucial for the high-rate and reliable continuous-wave mud pulse transmission system. However, its dynamic responses are constrained by resistant load shocks and harsh operating environments. This study proposes an enhanced nonlinear active disturbance rejection control (EADRC) that integrates cascaded extended state observer (CESO) and enhanced nonlinear state error feedback
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Design of a utility-based lane change decision making algorithm and a motion planning for energy-efficient highway driving Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-06 Sahar Zeinali, Michael Fleps-Dezasse, Julian King, Georg Schildbach
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A multi-platform Guidance, Navigation and Control system for the autosub family of Autonomous Underwater Vehicles Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-05 Davide Fenucci, Francesco Fanelli, Alberto Consensi, Georgios Salavasidis, Miles Pebody, Alexander B. Phillips
Over the last decade, there has been a proliferation of marine robots such as Unmanned Surface Vehicles (USVs), Autonomous Underwater Vehicles (AUVs) and underwater gliders. The variety of vehicles’ capabilities and styles has led to numerous strategies to address the Guidance, Navigation and Control (GNC) tasks. In particular, a recent trend in the advancements of GNC systems is to develop modular
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TFPred: Learning discriminative representations from unlabeled data for few-label rotating machinery fault diagnosis Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-05 Xiaohan Chen, Rui Yang, Yihao Xue, Baoye Song, Zidong Wang
Recent advances in intelligent rotating machinery fault diagnosis have been enabled by the availability of massive labeled training data. However, in practical industrial applications, it is often challenging and costly to annotate a large amount of data. To address the few-label fault diagnosis problem, a time–frequency prediction (TFPred) self-supervised learning framework is proposed to extract
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A coordinated framework of aerial manipulator for safe and compliant physical interaction Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-05 Qianyuan Liu, Shangke Lyu, Kexin Guo, Jianliang Wang, Xiang Yu, Lei Guo
The challenge of ensuring compliant behavior in aerial manipulators during physical interactions is addressed in this study. This work presents a coordinated interactive framework for aerial manipulators, specifically designed to ensure compliant physical interactions during contact with the surroundings. Without the reliance on force sensors, an external force estimator is employed to recognize interaction
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Vehicle Sideslip Angle estimation under critical road conditions via nonlinear Kalman filter-based state-dependent Interacting Multiple Model approach Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-04 Francesco Tufano, Dario Giuseppe Lui, Simone Battistini, Renato Brancati, Basilio Lenzo, Stefania Santini
The knowledge of Vehicle Sideslip Angle (VSA) can play an essential role in active safety vehicle control systems. However, due to the high costs of sensing instruments, this information is difficult to be directly measured onboard of series production vehicles, restricting its application in practice. It follows that there is a need for online VSA estimation methods only based on available measurements
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A navigation accuracy compensation algorithm for low-cost unmanned surface vehicles based on models and event triggers Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-04 Xin Yan, Xiaofei Yang, Beizhen Feng, Wei Liu, Hui Ye, Zhiyu Zhu, Hao Shen, Zhengrong Xiang
Integrated navigation is often used for navigation of unmanned surface vehicles (USVs). For a class of cost-sensitive USVs, it is desirable to compose integrated navigation by low-cost inertial navigation systems (INS) and global positioning systems (GPS). In the cases of GPS signal failure or interference, only INS onboard can be used for navigation, which often leads to the navigation accuracy deteriorating
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Non-linear model predictive control based trajectory tracking of hand and wrist motion using functional electrical stimulation Control Eng. Pract. (IF 4.9) Pub Date : 2024-03-04 Tarun Karak, Souvik Basak, Patrick A. Joseph, Somnath Sengupta
Functional Electrical Stimulation (FES) on muscles can recover voluntary motions of the upper limb paralysed patients, enabling them to conduct daily life activities like grasping, holding, etc. FES can stimulate the forearm muscles to track joint trajectory while avoiding hyper-stimulation. While using FES, model-based closed-loop control schemes can track the desired trajectory more effectively than
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Combined acceleration slip regulation for multi-wheel distributed electric drive vehicles considering torque loss factor Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-28 Zixian Li, Shiju Pan, Kang Mao, Youchun Xu
In this paper, we propose an acceleration slip regulation (ASR) method for multi-wheel distributed electric drive vehicles, which considers the torque loss factor and combines dynamics and stability control. The accurate estimation of the peak adhesion coefficient and optimal slip ratio on complex roads is a challenging task, resulting in uncertainties in the wheel slip domain, the timing of ASR activation
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Comparison of LQR with MPC in the adaptive stabilization of a glass conditioning process using soft-sensors for parameter identification and state observation Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-27 Witold Byrski, Michał Drapała, Jędrzej Byrski, Matti Noack, Johann Reger
The paper presents the comparison of two different continuous-time adaptive control strategies applied to the temperature stabilization of molten glass during conditioning. Both control methods include on-line linear continuous-time model parameter identification using a nonstandard procedure based on the modulating functions method. The related control task is of great practical importance because
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Control design for thrust generators with application to wind turbine wave-tank testing: A sliding-mode control approach with Euler backward time-discretization Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-26 Mohammad Rasool Mojallizadeh, Félicien Bonnefoy, Vincent Leroy, Franck Plestan, Sylvain Delacroix, Jérémy Ohana, Benjamin Bouscasse
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Adaptive feedforward control of sinusoidal disturbances with applications to electric propulsion systems Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-24 Henrik Mosskull, Bo Wahlberg
Generalized adaptive feedforward cancellation with a reference sensor is considered to specifically suppress second harmonic torque oscillations with an ac fed propulsion system for an electric train. A single complex-valued design parameter is tracked through gradient-type adaptation. Both Cartesian and polar parameter representations are considered, resulting in quite varying convergence properties
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Reagent dosage inference based on graph convolutional memory perception network for zinc roughing flotation Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-21 Can Tian, Zhaohui Tang, Hu Zhang, Yongfang Xie, Zhien Dai
In froth flotation, the precise presetting of reagent dosage is crucial for enhancing mineral recovery and flotation efficiency. Considering that the manual operation method is susceptible to some subjective factors, many machine vision-based intelligent reagent dosage presetting approaches are developed. However, prevailing presetting methods primarily rely on empirical knowledge, and ignore the potential
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A new adaptive feature fusion and selection network for intelligent transportation systems Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-20 Baoxin Shi, Yuanhong Liu, Shixiang Lu, Zhi-Wei Gao
Drive bearings, as essential components of vehicles, play a crucial role in ensuring the safety and reliability of intelligent transportation systems. By monitoring and analyzing the operating condition of drive bearings, it is possible to troubleshoot the transmission system and improve the service life of the vehicle. However, due to the complexity of monitoring devices, noise interference, and the
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Design of current-risk-aware disturbance rejection controller for speed regulation of PMSMs Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-15 Yuan Tan, Jun Yang, Jinhao Liu, Shihua Li
This paper presents a current-risk-aware disturbance rejection controller (CRA-DRC) for speed regulation of permanent magnet synchronous motors (PMSMs), enhancing their reliability and safety. The CRA-DRC considers a current-risk-aware constraint, which reduces the conservatism associated with hard current-constraint and expands the feasible region of operation. To estimate unmatched disturbances (external
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Unsupervised transfer autoencoder model based on adversarial strategy for non-linear process monitoring Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-13 Xu Yang, Jieshi Xiao, Jian Huang, Kaixiang Peng
In the industrial processes, the drift in operation conditions would cause the discrepancy of data distribution. In this study, an unsupervised transfer autoencoder model based on adversarial strategy is proposed to address the issue of model mismatch and to extract universal features. First, the unsupervised network is employed to training models to avoid the high cost associated with obtaining labelled
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An energy efficient fault-tolerant controller for homing of underactuated AUVs Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-13 Cristina Cerrada, Dictino Chaos, David Moreno-Salinas, António Pascoal, Joaquín Aranda
In the event of a failure that will prevent an Autonomous Underwater Vehicle (AUV) from executing a specified task, the vehicle must be recovered safely to avoid further damage to itself or to other vehicles/agents in the neighbourhood. Motivated by this operational requirement, this work presents an optimal fault-tolerant controller to drive an underactuated AUV to a recovery point (so-called automatic
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Control of the launch and recovery of small boats to a mothership in high sea states using sliding mode methods Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-13 Vikram Rout, Cleo Vile, Christopher Edwards, Michael J. Belmont, Guang Li, Dominic Taunton
The launch and recovery (L&R) of a small vessel from a large mothership occurs in various settings, such as the rescue of stranded personnel, extraction of unmanned autonomous sea monitoring sensors and the deployment of rescue submersibles. L&R of a small vessel, from a large mothership, at high sea states is difficult and is often avoided for safety reasons. This paper proposes sliding mode controllers
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AI-MOLE: Autonomous Iterative Motion Learning for unknown nonlinear dynamics with extensive experimental validation Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-10 Michael Meindl, Simon Bachhuber, Thomas Seel
This work proposes (AI-MOLE), a method that enables systems with unknown, nonlinear dynamics to autonomously learn to solve reference tracking tasks. The method iteratively applies an input trajectory to the unknown dynamics, trains a Gaussian process model based on the experimental data, and utilizes the model to update the input trajectory until desired tracking performance is achieved. Unlike existing
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EPBS_FIDMV: A fault injection and diagnosis methods validation benchmark for EPBS of EMU Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-09 Zhiwen Chen, Lijuan Peng, Jingke Fan, Haoxiang Liang, Hao Luo, Chao Cheng, Zhiyong Chen
The electro-pneumatic brake system (EPBS) is an essential part of electric multiple units. Fault diagnosis (FD) methods play an important role in the safe operation of EPBS, and have been active research direction. The literature is considerably on studies concerned with new fault diagnosis methods, while how to quantitatively validate these methods for EPBS is quite few. The main attribute is the
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Impact of Wind and Wind Shear on Sliding Mode Controller Assisted Aircraft Spin Recovery Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-07 Salahudden Salahudden
The problem of aircraft spin recovery in the presence of wind and wind shear is addressed in this work. Three different scenarios for the wind are considered: fixed direction and fixed speed, fixed direction and variable speed, and variable direction and fixed speed. First, a mathematical wind and wind shear model is constructed and integrated into the aircraft's equations of motion. The flight simulation
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Parameterised function ILC with application to stroke rehabilitation Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-07 Xiaoru Sun, Chris T. Freeman
Functional electrical stimulation (FES) is a popular assistive technology that uses electrical impulses to artificially stimulate muscles to help paralysed or impaired subjects regain their lost movement after stroke. A large number of FES elements can be combined to form FES arrays which are capable of activating the multiple muscles needed to perform functional arm movements. However, the control
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Variable gain ADRC for delta parallel manipulators with disturbances Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-07 Shaomeng Gu, Jinhui Zhang
In this paper, a variable gain active disturbance rejection control (VGADRC) method is proposed for solving the trajectory tracking problem of delta parallel manipulators with disturbances. The VGADRC, including variable gain tracking differentiator (VGTD), variable gain extended state observer (VGESO), and variable gain controller (VGC), incorporates error-based variable gains to improve the control
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Enhanced control in time-delay processes: Diagnostic, monitoring, and self-tuning strategies for the filtered smith predictor in response to model-plant mismatch and abrupt load disturbances Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-06 Sergio A.C. Giraldo, Príamo A. Melo, Argimiro R. Secchi
The Filtered Smith Predictor (FSP) is a practical structure in industrial control systems, especially those with dominant time delays. Despite its importance, a notable gap exists in developing tailored algorithms for the FSP that can effectively diagnose model degradation and the presence of abrupt disturbances. This research addresses the challenge of distinguishing between model-plant mismatch (MPM)
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Sampled-data robust control of a 2-DoF helicopter modeled using a quasi-LPV framework Control Eng. Pract. (IF 4.9) Pub Date : 2024-01-31 Julio Yuzo Yassuda, Cristiano Marcos Agulhari, Emerson Ravazzi Pires da Silva
The development of a sampled-data robust controller, applied to a 2-DoF helicopter system, is proposed in this paper. The helicopter presents a nonlinear dynamics, which is modeled in this paper using a quasi-LPV approach, thus allowing the application of convex LMI conditions for the determination of the desired controllers. The robustness against effects such as sampling rate variation, noise and
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Encrypted distributed model predictive control of nonlinear processes Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-01 Yash A. Kadakia, Fahim Abdullah, Aisha Alnajdi, Panagiotis D. Christofides
In this research, we present an encrypted iterative distributed model predictive controller (DMPC) to enhance the computational efficiency and cybersecurity of large-scale nonlinear processes. In this configuration, a single large process is divided into numerous smaller subsystems, each regulated by a unique Lyapunov-based MPC (LMPC) that utilizes the complete process model and exchanges control inputs
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Real-time estimation of the optimal longitudinal slip ratio for attaining the maximum traction force Control Eng. Pract. (IF 4.9) Pub Date : 2024-02-01 David Vošahlík, Tomas Hanis
Advanced driver assistant systems in vehicles, such as anti-lock brake system, electronic stability program, and traction control, heavily rely on the traction force of the wheels, which is determined by the wheels’ longitudinal slip ratio. A common method used to describe this dependency is the well-known Pacejka (magic) formula. The Pacejka (magic) formula suggests the existence of a unique optimal
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Automatic target recognition and geolocalisation of natural gas seeps using an autonomous underwater vehicle Control Eng. Pract. (IF 4.9) Pub Date : 2024-01-28 Matteo Bresciani, Leonardo Zacchini, Alberto Topini, Alessandro Ridolfi, Riccardo Costanzi
Autonomous Underwater Vehicles (AUVs) have proven to be a precious resource for oceans preservation thanks to their ability to accomplish survey missions on wide areas without the need of human supervision. This also includes the detection and mapping of underwater gas emissions, whether these are due to damaged offshore structures or naturally released from the seafloor. Indeed, submarine seepage
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Unsupervised learning of part-based representations using sparsity optimized auto-encoder for machinery fault diagnosis Control Eng. Pract. (IF 4.9) Pub Date : 2024-01-28 Zhiqiang Zhang, Yuxiang Shen, Shuiqing Xu
Unsupervised feature learning (UFL) has gained a growing attention in machinery fault diagnosis because of its great advancement in adaptively learning useful features over traditionally designing hand-crafted features. Since there is no available prior knowledge about the health labels, sparsity becomes the key to promote feature discrimination. In this paper, a new UFL method called sparsity optimized
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Wind-load estimation for seismically isolated building by equivalent-input-disturbance approach with robust-control strategy Control Eng. Pract. (IF 4.9) Pub Date : 2024-01-25 Kou Miyamoto, Jinhua She, Daiki Sato, Yinli Chen, Razelle Dennise A. Soriano, Satoshi Nakano
This paper presents a new method that uses the equivalent-input-disturbance (EID) approach to estimate the wind load of a seismically isolated building. To verify the control performance of wind-resistant design methods and devices, wind-load data are important for structural design of skyscrapers. However, wind loads cannot be measured directly and is usually estimated based on structural responses