Tiexiong Huang , Dayong Li , Juan Lu , Xiaoxue Luo , Wei He
{"title":"Robust temperature control of a diesel oxidation catalyst using continuous terminal sliding mode with extended state observer","authors":"Tiexiong Huang , Dayong Li , Juan Lu , Xiaoxue Luo , Wei He","doi":"10.1016/j.conengprac.2025.106316","DOIUrl":"10.1016/j.conengprac.2025.106316","url":null,"abstract":"<div><div>Robust temperature control is essential for the diesel oxidation catalyst (DOC) in modern diesel engines to realize efficient and reliable thermal regenerations in real driving cycles. This paper investigates the design and validation of an improved robust control solution for the DOC-outlet temperature control by applying the error-based active disturbance rejection control (ADRC) method and the non-singular terminal sliding mode (TSM) scheme along with a second-order sliding mode approach. The second-order TSM scheme is introduced to substitute the proportional–derivative (PD) control in the conventional ADRC framework. A finite-time convergence of the sliding mode dynamics is consequently guaranteed and the tracking errors are driven to zeros asymptotically, which accordingly implies that a faster temperature response is expected. Moreover, the undesired chattering effect is eliminated, resulting in an inherently continuous control input signal. The extended state observer (ESO) is synthesized as a feedforward compensator to estimate and reject the total disturbance. Theoretical convergence and stability of the proposed control strategy are analyzed based on the Lyapunov approach. Selection of the controller parameters is further discussed as well. The effectiveness and robustness are finally examined through an extensive comparative study using simulation and experimental tests. Results demonstrate that the proposed continuous TSM control achieves superior temperature control performance, including faster disturbance suppression, more accurate set-point tracking, and greater robustness against internal model uncertainties and external disturbances compared to the conventional ADRC controller.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106316"},"PeriodicalIF":5.4,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629183","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":"Bumpless transfer control for DC-DC buck-boost converter modeled by switched affine systems","authors":"Xiaozeng Xu , Yanzheng Zhu , Fen Wu , Xinkai Chen , Chun-Yi Su","doi":"10.1016/j.conengprac.2025.106320","DOIUrl":"10.1016/j.conengprac.2025.106320","url":null,"abstract":"<div><div>This study focuses on the bumpless transfer control for a DC-DC buck-boost converter, which is modeled as a class of discrete-time switched affine systems. While achieving smooth transitions between operating modes is a well-established goal in the literature, this work introduces a novel approach to tackle these challenges through innovative methodologies. A shifted-point-dependent controller and a state-dependent switching law are developed, ensuring convergence to a union of regions encompassing shifted points and mitigating oscillations during switching events. A novel multi-shifted-point-dependent Lyapunov functional is proposed, integrating bump limitation constraints, and sufficient conditions are derived for the solvability of the bumpless transfer control problem. Furthermore, the methodology is generalized to switched affine systems with uncertainties, and the corresponding robust stability conditions are provided. Finally, the superiority of the proposed approach is demonstrated through a experimental verification of a DC-DC buck-boost converter.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106320"},"PeriodicalIF":5.4,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629182","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}
Yitao Luo , Runde Zhang , Zhuyun Chen , Chong Xie , Shaowu Zheng , Shanhu Yu , Weihua Li
{"title":"Enhanced deep reinforcement learning model with bird’s eye view design strategy for decision control in vehicle-road collaboration","authors":"Yitao Luo , Runde Zhang , Zhuyun Chen , Chong Xie , Shaowu Zheng , Shanhu Yu , Weihua Li","doi":"10.1016/j.conengprac.2025.106315","DOIUrl":"10.1016/j.conengprac.2025.106315","url":null,"abstract":"<div><div>Autonomous driving in complex traffic scenarios is a vital challenge, and deep reinforcement learning (DRL) has been extensively applied to address this issue. The recent advancement of vehicle-to-everything (V2X) technology has provided abundant perceptual information for DRL agents, improving the accuracy and safety of decision control. However, existing research on green wave traffic scenes has difficulty adapting to multi-signal scenarios with single-signal countdown models, which lack complete signal state information. To address this limitation, an enhanced DRL model with bird’s eye view (BEV) design strategy is proposed for vehicle-road collaborative autonomous driving scenarios. The constructed model introduces a state prediction fusion strategy to compensate for state information. Specifically, state information is first predicted by fusing perception results from vehicles and roadside units (RSUs) at different moments. Then, the recommended velocity is derived for green wave passage, called the green wave velocity belt, and incorporate it into the state space as two variables in the state vector. Finally, a relevant reward term in the reward function is designed to guide agent learning strategies. The proposed method is trained on the basis of the parallel DreamerV3 framework. The results show that the proposed approach can effectively integrate multi-source perceptual information, improving training efficiency and control performance, and demonstrating great effectiveness and practical application value.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106315"},"PeriodicalIF":5.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620563","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}
Caixin Fu , Changhong Jiang , Zhiwei Wan , Qiang Wang , Shenquan Wang
{"title":"A robust distributed fault detection scheme for interconnected systems based on subspace identification technique","authors":"Caixin Fu , Changhong Jiang , Zhiwei Wan , Qiang Wang , Shenquan Wang","doi":"10.1016/j.conengprac.2025.106301","DOIUrl":"10.1016/j.conengprac.2025.106301","url":null,"abstract":"<div><div>This paper proposes a robust data-driven distributed fault detection (FD) method for interconnected systems with stochastic noises, addressing the challenges posed by stochastic noises and the limitations of centralized designs on real industrial systems. The proposed method utilizes the process data from a sensor network to generate robust residual signals for FD. The method performs distributed calculations of residual signals and test statistics at each sensor node using the subspace identification technique and the average consensus algorithm. To ensure satisfactory detection performance and robustness against uncertainties caused by stochastic noises, the paper integrates the performance index and the Mahalanobis distance into the FD framework. Unlike existing FD methods that rely on the Mahalanobis distance, this study also explores improving detection performance through the consensus algorithm and performance index. It is worth noting that this method not only mitigates the negative effects of stochastic noises in FD, but also eliminates global communication costs and complex information interactions. The developed method is validated through an experimental study on a real traction drive system to assess its feasibility and effectiveness.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106301"},"PeriodicalIF":5.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620564","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}
Xiaochao Liu , Xuefeng Sun , Zhuangzhuang Wang , Ning Bai , Yaoxing Shang
{"title":"Adaptive aircraft anti-skid braking control for runway disturbance compensation","authors":"Xiaochao Liu , Xuefeng Sun , Zhuangzhuang Wang , Ning Bai , Yaoxing Shang","doi":"10.1016/j.conengprac.2025.106314","DOIUrl":"10.1016/j.conengprac.2025.106314","url":null,"abstract":"<div><div>During aircraft braking, the wheels are often in a high-slip state, making them prone to repeated skidding under the influence of internal and external disturbances. Therefore, designing a disturbance-resistant anti-skid braking control system is key to achieving efficient braking. This paper proposes an adaptive runway disturbance-resistant anti-skid braking control law that addresses the problem of skidding caused by various disturbances during aircraft braking, thereby improving braking efficiency. By studying the internal and external disturbances affecting the aircraft during braking, these disturbances are classified based on their impact on the balance point of the wheel slip system. A method based on the induced ideal limit cycle is proposed to detect disturbances. An adaptive braking control strategy incorporating runway recognition technology was developed, enabling the braking system to adjust the target deceleration rate according to real-time disturbances. Finally, simulation tests and inertial platform tests confirmed that the proposed control law significantly improves efficiency compared to the PBM (Press Bias Module) control method.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106314"},"PeriodicalIF":5.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620645","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 da F. Pereira , Rodolfo C.C. Flesch , Gabriel Thaler
{"title":"Induction heating using MPC and state estimation for safe acceleration of compressor tests","authors":"Guilherme da F. Pereira , Rodolfo C.C. Flesch , Gabriel Thaler","doi":"10.1016/j.conengprac.2025.106317","DOIUrl":"10.1016/j.conengprac.2025.106317","url":null,"abstract":"<div><div>Induction heating (IH) systems normally do not use closed-loop temperature control, but the results in some applications can be considerably improved by using a controller. The objective of this work is to experimentally assess the use of zone model-based predictive controllers (ZMPCs) for temperature control in an IH prototype used to heat a compressor in performance tests with constraints on unmeasured states. This choice was motivated by the importance of such tests in industry, the potential to shorten the transient duration using IH, and the existence of safety constraints on non-measurable temperatures. A test rig with an instrumented compressor was built to test the proposed framework with different controllers from the literature, including a reference-tracking model-based predictive controller (MPC) predictive controller (MPC) and a PI controller. A state-space model was identified using measured temperatures as states to describe the thermal dynamics of the compressor. Since the temperature required for ensuring safety constraints is not measurable in a regular compressor, a Kalman filter was used for state estimation. Experimental results show that all controllers satisfy the constraints and can track a reference step with zero steady-state error. The best result was achieved by ZMPC, where the heating time of the evaluated compressor was reduced from 70<!--> <!-->min to less than 10<!--> <!-->min while maintaining safe internal temperature conditions, which represents a reduction of approximately 90% in transient time.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106317"},"PeriodicalIF":5.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620644","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}
He Ren , Min Zhuang , Lingfang Sun , Huichao Ji , Xiuyu Zhang , Chun-Yi Su
{"title":"Two-stage three-phase photovoltaic grid-connected inverter control method based on off-policy integral reinforcement learning","authors":"He Ren , Min Zhuang , Lingfang Sun , Huichao Ji , Xiuyu Zhang , Chun-Yi Su","doi":"10.1016/j.conengprac.2025.106313","DOIUrl":"10.1016/j.conengprac.2025.106313","url":null,"abstract":"<div><div>In this article, a novel control method of the grid-connected inverter (GCI) based on the off-policy integral reinforcement learning (IRL) method is presented to solve two-stage three-phase photovoltaic (TTP) power quality degradation problem of the grid connection caused by unknown system dynamics. Firstly, the voltage-current dual-loop control (VDC) structure is adopted, where the model of the current loop is restructured benefitting from the current tracking principle. Secondly, the grid-connected power quality problem is turned into a zero-sum game (ZSG) problem, which can be completed by solving the Hamilton–Jacobi-Bellman (HJB) equations using the off-policy IRL method only with the collected input and output (I/O) data. Thirdly, the off-policy IRL method is improved on the basis of the traditional policy iteration method and the equivalence between them is demonstrated. Finally, the presented method is verified by StarSim Modeling Tech power electronic simulation experiment platform to satisfy the standard of the grid connection and the total harmonic distortion of the current is less than 5%.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106313"},"PeriodicalIF":5.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600935","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}
Maria Camila Merchán-Riveros, Carolina Albea, Franciso Salas
{"title":"Three-time-scale control for discharging rate consensus and large-signal stability analysis in AC-bus microgrids","authors":"Maria Camila Merchán-Riveros, Carolina Albea, Franciso Salas","doi":"10.1016/j.conengprac.2025.106299","DOIUrl":"10.1016/j.conengprac.2025.106299","url":null,"abstract":"<div><div>A distributed control scheme for islanded AC-bus microgrids is proposed, based on multi-agent system and singular perturbation theory. The goal is to achieve a balanced State Of Charge (SOC) for each Battery Energy Storage System (BESS) in discharging mode, ensuring stability properties of a large-signal model that considers the primary and secondary control loop dynamics. The power inverters are controlled through a voltage and current loop. Moreover, a droop control and consensus algorithm are proposed to ensure that the SOC of these BESSs are balanced. Furthermore, large-signal stability analysis is assessed for the complete network system by using singular perturbation theory. Indeed, through an appropriate selection of the parameters, the dynamics exhibit three-time-scale separation to fit each control goal (power converter control, droop control and consensus control). Experimental results on an Imperix power test bench validate the proposed control scheme, and verify the reliability and robustness with respect to any connection/disconnection event or communication failure through different scenarios.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106299"},"PeriodicalIF":5.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143590355","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":"Real-time kinematics-based sensor-fault detection for autonomous vehicles using single and double transport with adaptive numerical differentiation","authors":"Shashank Verma, Dennis S. Bernstein","doi":"10.1016/j.conengprac.2025.106304","DOIUrl":"10.1016/j.conengprac.2025.106304","url":null,"abstract":"<div><div>Sensor-fault detection is crucial for the safe operation of autonomous vehicles. This paper introduces a novel kinematics-based approach for detecting and identifying faulty sensors, which is model-independent, rule-free, and applicable to ground and aerial vehicles. This method, called kinematics-based sensor fault detection (KSFD), relies on kinematic relations, sensor measurements, and real-time single and double numerical differentiation. Using onboard data from radar, rate gyros, magnetometers, and accelerometers, KSFD identifies a single faulty sensor in real time. To achieve this, adaptive input and state estimation (AISE) is used for real-time single and double numerical differentiation of the sensor data, and the kinematically exact single and double transport theorems are used to evaluate the consistency of the data. Unlike model-based and knowledge-based methods, KSFD relies solely on sensor signals, kinematic relations, and AISE for real-time numerical differentiation. For ground vehicles, KSFD requires six kinematics-based error metrics, whereas, for aerial vehicles, nine error metrics are needed. Simulated and experimental examples are provided to evaluate the effectiveness of KSFD.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106304"},"PeriodicalIF":5.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143579524","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":"FPGA implementation of edge-side motor fault diagnosis using a Kalman filter-based empirical mode decomposition algorithm","authors":"Jiaxin Li, Maosong Cheng, Yongbo Wei, Zhimin Dai","doi":"10.1016/j.conengprac.2025.106312","DOIUrl":"10.1016/j.conengprac.2025.106312","url":null,"abstract":"<div><div>Despite the successful use of deep learning in motor fault diagnosis, its real-time applications have been greatly hindered due to the enormous computational burden and extensive processing time. Addressing this, a Kalman filter-based empirical mode decomposition (KF-EMD) algorithm is proposed, replacing the cubic spline interpolation of traditional EMD with a Kalman filter for real-time FPGA (Field Programmable Gate Array) processing. This algorithm enhances the detection of data anomalies and reduces the computational burden on a lightweight multilayer perceptron (MLP) model, which recognizes features extracted by KF-EMD at fixed intervals. The proposed real-time fault diagnosis method achieved 98.96% accuracy on the Case Western Reserve University (CWRU) dataset and 98.05% on our motor diagnosis experimental platform.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106312"},"PeriodicalIF":5.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563162","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}