Control Engineering Practice最新文献_第6页

Recursive total least squares with improved parameter tracking: Application to model-based vehicle mass estimation 改进参数跟踪的递归总最小二乘：在基于模型的车辆质量估计中的应用

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-20 DOI: 10.1016/j.conengprac.2025.106429

Hugo Koide , Jérémy Vayssettes , Guillaume Mercère

{"title":"Recursive total least squares with improved parameter tracking: Application to model-based vehicle mass estimation","authors":"Hugo Koide , Jérémy Vayssettes , Guillaume Mercère","doi":"10.1016/j.conengprac.2025.106429","DOIUrl":"10.1016/j.conengprac.2025.106429","url":null,"abstract":"<div><div>Vehicle mass plays an influential role in various dynamical systems for vehicle safety and control. In this work, a novel recursive total least squares (RTLS) solution is presented for the online estimation of gross vehicle mass. The proposed method requires access to engine torque, engine speed, wheel speed, and vehicle IMU acceleration measurements. Different algorithm configurations are considered for mass estimation of internal combustion engine and electric vehicles, with a focused application to passenger cars and light commercial vehicles. The baseline RTLS algorithm is improved by means of regularization, outlier attenuation, parameter projection, and enhanced tracking of jumping parameters, all of which play an important role in optimizing estimator performance for industrial applications. The proposed algorithm is then generalized to account for heterogeneous and heteroscedastic measurement noise with a recursive noise covariance estimation algorithm. The method is tested against two well-known benchmark algorithms from the mass estimation literature with experimental electric vehicle data, and solution sensitivity to model assumptions and model input parameters is discussed. The vehicle experiments show that the proposed method outperforms the benchmark methods in terms of accuracy and convergence characteristics.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106429"},"PeriodicalIF":5.4,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330860","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

Non-parametric system norm estimation of multivariable systems 多变量系统的非参数系统范数估计

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-19 DOI: 10.1016/j.conengprac.2025.106421

Paul Tacx , Tom Oomen

引用次数: 0

Modeling and validation of a clinker production process model that captures the coupled internal dynamics 捕获耦合内部动力学的熟料生产过程模型的建模和验证

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-19 DOI: 10.1016/j.conengprac.2025.106438

Melih Turkseven, Muhammad Aslani Moghanloo

{"title":"Modeling and validation of a clinker production process model that captures the coupled internal dynamics","authors":"Melih Turkseven, Muhammad Aslani Moghanloo","doi":"10.1016/j.conengprac.2025.106438","DOIUrl":"10.1016/j.conengprac.2025.106438","url":null,"abstract":"<div><div>Cement clinker production is an energy-intensive process that accounts for a substantial share of global industrial energy consumption. Model predictive control (MPC) is commonly used to regulate this process, requiring a compact control-oriented model that describes the input–output relationships of the production system. A prevalent method for obtaining such a model is to identify direct input–output relationships. However, this approach often overlooks the coupled dynamics of internal process variables, which can limit prediction accuracy. This study introduces a methodology for mapping these dynamically coupled internal variables by modeling the production process as a network of interconnected chambers. A discrete-linear model that captures these couplings is then developed using data collected from an operational clinker plant. The proposed model is evaluated against widely-used linear modeling approaches, with a focus on multi-step-ahead prediction performance, a metric often neglected in the literature. Eight key variables were chosen as targets for prediction, and the proposed model consistently outperformed the alternatives in predicting their variations, particularly when the prediction horizon exceeded five sampling intervals. An MPC implementation of the proposed model is provided for illustrating its potential use.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106438"},"PeriodicalIF":5.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322494","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

MPC-based postural control: Mimicking CNS strategies for head–neck stabilization under eyes closed conditions 基于mpc的姿势控制：闭眼条件下头颈部稳定的模仿中枢神经系统策略

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-19 DOI: 10.1016/j.conengprac.2025.106428

Chrysovalanto Messiou, Riender Happee, Georgios Papaioannou

{"title":"MPC-based postural control: Mimicking CNS strategies for head–neck stabilization under eyes closed conditions","authors":"Chrysovalanto Messiou, Riender Happee, Georgios Papaioannou","doi":"10.1016/j.conengprac.2025.106428","DOIUrl":"10.1016/j.conengprac.2025.106428","url":null,"abstract":"<div><div>A plausible explanation about the acquisition and realization of beliefs by the central nervous system (CNS) when issuing control actions to counteract external perturbations, is to employ mechanisms aiming to minimize sensory conflict and muscle effort while maintaining biomechanical stability. However, existing head–neck postural control models fail to explicitly integrate this plausible CNS objective within their stabilization mechanisms. This study proposes a novel Model Predictive Control (MPC)-based framework to replicate CNS postural stabilization by incorporating the minimization of sensory conflict as a primary control objective through the MPC cost function. The MPC is integrated in a simplified biomechanical head–neck structure, using a prediction model and sensory feedback to optimize control actions over a finite time horizon within biomechanical constraints. Two human experiments measuring head motion with unpredictable seat and trunk perturbations were used to evaluate and validate different configurations of sensory feedback pathways. During anterior–posterior translational trunk perturbations, the results illustrated that the configuration with vestibular feedback improved head position prediction while muscle effort and partial somatosensory feedback alone, achieved superior results in head pitch prediction. Meanwhile, muscle effort and partial somatosensory feedback were sufficient to stabilize the head during trunk rotational (pitch) perturbations. Finally, a multi-scenario optimization demonstrated that a single set of MPC weights could generalize stabilization across both perturbation types. The results demonstrate the effectiveness of MPC in replicating CNS-inspired postural adjustments, indicating that controlling a simplified biomechanical head–neck model provides a computationally efficient and accurate alternative to complex multi-segment approaches.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106428"},"PeriodicalIF":5.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313633","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

Resource-efficient direct yaw moment control for four-wheel independent drive electric vehicles based on dual event-triggered adaptive dynamic programming with off-policy mechanism 基于非策略双事件触发自适应动态规划的四轮独立驱动电动汽车资源节约型直接偏航力矩控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-19 DOI: 10.1016/j.conengprac.2025.106437

Xingqi Hua, Pak Kin Wong, Jing Zhao

{"title":"Resource-efficient direct yaw moment control for four-wheel independent drive electric vehicles based on dual event-triggered adaptive dynamic programming with off-policy mechanism","authors":"Xingqi Hua, Pak Kin Wong, Jing Zhao","doi":"10.1016/j.conengprac.2025.106437","DOIUrl":"10.1016/j.conengprac.2025.106437","url":null,"abstract":"<div><div>This paper aims to design a resource-efficient direct yaw moment control (DYC) scheme for four-wheel independent drive electric vehicles using reinforcement learning. Firstly, the DYC problem is constructed based on the nonlinear vehicle model and described as an optimization problem by constructing performance indicators and Hamiltonian functions. Then, a dual event-triggered mechanism is proposed to save communication and computational costs. Next, the Hamilton–Jacobi–Bellman equation of the optimization problem is constructed using the adaptive dynamic programming method. Furthermore, an experience replay buffer incorporating dual historical data is designed for weight iteration to relax the persistence of excitation condition and eliminate the need for importance sampling. Finally, the approximate optimal control law is obtained through online tuning with an off-policy mechanism. Simulation and multiple hardware-in-the-loop tests demonstrate that the proposed scheme is robust and effectively enhances vehicle lateral stability while reducing communication and computational costs by approximately 75% and 25%, respectively, compared to traditional time-triggered methods.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106437"},"PeriodicalIF":5.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313634","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

Finite-time image-based visual servoing with field of view and performance constraints 具有视场和性能约束的有限时间图像视觉伺服

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-17 DOI: 10.1016/j.conengprac.2025.106433

Jianfei Lin, Lei Ma, Deqing Huang, Dongrui Wang, Wenru Lu

引用次数: 0

Entropy-based controller parameter optimization for a dual-input EV charger integrated with WPT and solar energy using the Whale Optimization Algorithm 基于熵的WPT -太阳能双输入电动汽车充电器控制器参数Whale优化算法

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-17 DOI: 10.1016/j.conengprac.2025.106432

M. Ganesh Babu , P. Srinivasa Rao Nayak

{"title":"Entropy-based controller parameter optimization for a dual-input EV charger integrated with WPT and solar energy using the Whale Optimization Algorithm","authors":"M. Ganesh Babu , P. Srinivasa Rao Nayak","doi":"10.1016/j.conengprac.2025.106432","DOIUrl":"10.1016/j.conengprac.2025.106432","url":null,"abstract":"<div><div>Charging electric vehicle (EV) batteries at constant voltage (CV) is essential for extending battery life and improving energy transfer efficiency. However, conventional PI controllers face challenges in maintaining voltage regulation under varying input conditions, such as wireless power transfer (WPT) misalignments and photovoltaic (PV) irradiance fluctuations, leading to poor transient performance. This paper presents an advanced control strategy that integrates WPT and rooftop solar input through a dual-input DC-DC converter (DIC) operating in closed-loop buck-boost mode. A PI controller regulates the output voltage, with its gains optimized using the Whale Optimization Algorithm (WOA). The controller is designed to minimize the Integral of Time-weighted Absolute Error (ITAE), settling time, and transient overshoot, forming a multi-objective optimization problem. The Entropy method is employed to assign weights to the objectives and construct a unified cost function. The proposed WOA-based controller is benchmarked against the JAYA algorithm, showing superior performance in reducing transient errors and improving system stability. The methodology is validated through MATLAB/Simulink simulations and experimental implementation on an FPGA-based platform. Controller performance is evaluated under dynamic WPT and PV conditions, demonstrating robustness and efficiency across multiple operating modes. Additionally, the impact of transient behavior on the battery’s state of health (SOH) is analyzed, indicating reduced degradation during charging. The results confirm that the proposed control strategy ensures reliable, efficient charging for next-generation EV systems integrating renewable energy sources.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106432"},"PeriodicalIF":5.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297969","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

Event-triggered sliding mode kinematic control for a four-wheeled steerable mobile robot using barrier-function-based variable gain 基于障碍函数变增益的事件触发滑模移动机器人运动学控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-17 DOI: 10.1016/j.conengprac.2025.106436

Hao Wu , Shuting Wang , Yuanlong Xie , Hu Li , Sheng Quan Xie , Shiqi Zheng , Yiming Yan

{"title":"Event-triggered sliding mode kinematic control for a four-wheeled steerable mobile robot using barrier-function-based variable gain","authors":"Hao Wu , Shuting Wang , Yuanlong Xie , Hu Li , Sheng Quan Xie , Shiqi Zheng , Yiming Yan","doi":"10.1016/j.conengprac.2025.106436","DOIUrl":"10.1016/j.conengprac.2025.106436","url":null,"abstract":"<div><div>Limited communication resources pose challenges to the stable control of uncertain mobile robots, especially for a four-wheeled steerable mobile robot (FSMR) with multiple sensors and actuators. This paper proposes an event-triggered sliding mode kinematic control scheme using barrier-function (BF)-based variable gain for FSMR under kinematic uncertainties and communication resources constraints. First, a novel positive-defined adjustable BF (PABF) is designed, confining the sliding variables within the predefined barrier. The given BF accommodates the aperiodic sampling, eliminating the necessity of small sampling intervals in the existing sliding mode. Then, a mixed event trigger mechanism includes the guarantees of stability and boundness of sliding variable errors, which reduces the frequency of control updates and serves as a critical element for ensuring the existence of a practical sliding mode (PSM). The preset bandwidth of PSM can be adjusted by the predefined barrier. Comparative analysis verify that the PABF enlarges the state-barrier margin, removing the need for small sampling steps. Finally, simulations and experiments demonstrate the proposed method achieves the predefined PSM band with smaller state errors. The total communication resources usage ratio is less than the compared method through a reduced number of events.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106436"},"PeriodicalIF":5.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307210","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

Distributed modeling and hybrid triggered coordination: A modular synthesis of X-by-wire actuators for high performance vehicular control 分布式建模和混合触发协调：用于高性能车辆控制的线传x传执行器的模块化综合

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-17 DOI: 10.1016/j.conengprac.2025.106440

Haoran Lv , Fankai Zhou , Chen Tang , Wenchao Tang , Lu Xiong

{"title":"Distributed modeling and hybrid triggered coordination: A modular synthesis of X-by-wire actuators for high performance vehicular control","authors":"Haoran Lv , Fankai Zhou , Chen Tang , Wenchao Tang , Lu Xiong","doi":"10.1016/j.conengprac.2025.106440","DOIUrl":"10.1016/j.conengprac.2025.106440","url":null,"abstract":"<div><div>X-by-wire chassis provides an ideal platform for enhancing vehicle stability. However, as the number of actuators increases, the growing complexity of control structure makes it challenging to balance control adaptability and performance. This paper adopts distributed model predictive control to tackle the modular control allocation problem for X-by-wire actuators. By incorporating characteristics of each actuator into distributed models of chassis subsystems, it addresses the challenge of plug-and-play modeling for heterogeneous subsystems. An consensus algorithm for distributed chassis control is then designed to handle coupled constraints and ensure overall vehicular performance under extreme conditions. To further improve computational efficiency in solving the distributed chassis control problem, a hybrid triggered coordination strategy is proposed. Both actuator response characteristics and vehicle stability criteria are considered in scheduling optimal trigger time of distributed actuators. Finally, simulation and experimental results demonstrate that the proposed algorithm significantly enhances the control performance of the chassis system under extreme conditions while achieving substantially higher computational efficiency compared to conventional centralized algorithms.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106440"},"PeriodicalIF":5.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297972","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

MOBIL-based traffic prediction and interaction-aware Model Predictive Control for autonomous highway driving 基于移动通信的交通预测与交互感知模型预测控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-06-17 DOI: 10.1016/j.conengprac.2025.106434

Xiaorong Zhang , Sahar Zeinali , Haowei Wen , Georg Schildbach

{"title":"MOBIL-based traffic prediction and interaction-aware Model Predictive Control for autonomous highway driving","authors":"Xiaorong Zhang , Sahar Zeinali , Haowei Wen , Georg Schildbach","doi":"10.1016/j.conengprac.2025.106434","DOIUrl":"10.1016/j.conengprac.2025.106434","url":null,"abstract":"<div><div>This paper proposes an interaction-aware Model Predictive Control (MPC) approach for autonomous highway driving, introducing a novel framework to model vehicle interactions. First, the possible lateral motion behaviors of the autonomous vehicle and surrounding vehicles are predicted using the rule-based Minimizing Overall Braking Induced by Lane Change (MOBIL) model, which evaluates actions based on their overall benefit to traffic flow. These predicted behaviors are then categorized according to the lateral motion of the autonomous vehicle. Based on this categorization, different MPC control modes are developed for each category. Finally, by solving the MPC optimization problems for all control modes and selecting the one that minimizes the overall cost for all vehicles, the lateral motion decision of the autonomous vehicle is determined. In each control mode, the autonomous and surrounding vehicles interact longitudinally to ensure collision avoidance, while simultaneously considering traffic rules and driving comfort. The proposed controller is validated in a high-fidelity IPG CarMaker and Simulink co-simulation environment across diverse cases, as well as in a Monte Carlo simulation study. Results show that the autonomous vehicle can perform safely and improve traffic flow by changing lanes when necessary. Monte Carlo simulations further demonstrate the robustness and generality of the proposed method across various traffic conditions.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"164 ","pages":"Article 106434"},"PeriodicalIF":5.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297971","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