{"title":"Adaptive fault-tolerant observer-based control for multi-input multi-output interconnected systems with bandwidth-limited communication","authors":"Aref Ghoreishee , Masoud Soroush","doi":"10.1016/j.conengprac.2024.106217","DOIUrl":"10.1016/j.conengprac.2024.106217","url":null,"abstract":"<div><div>The intensification of distributed manufacturing processes often increases the level of process interconnectivity, which subsequently leads to more intricate and complex process dynamics. Furthermore, wireless communication between processes and their controllers requires signal quantization. Motivated by these, this work presents an adaptive finite-time fault-tolerant observer-based quantized controller for a class of nonlinear state-delayed interconnected switched multi-input multi-output systems subject to arbitrary switching, quantized control and sensor signals, actuator and sensor faults, and nonlinear actuator behavior. The controller is tailored for interconnected distributed manufacturing processes with limited bandwidth communication channels for signal transmission. Sensor-fault-model parameters are estimated using a new adaptation law. Distributed observers are designed based on sensor-fault parameter estimates, the quantized faulty sensor data, and the quantized control signal. Nonlinear actuator behaviors including saturation, back-lash, and hysteresis are considered. The unknown nonlinear behavior of each subsystem is approximated using radial basis function neural networks. Using the Lyapunov-Razumikhin approach and an appropriate common Lyapunov function, the stability of the closed-loop system and the convergence of the tracking error to a desired neighborhood of the origin within a finite time are proved. The effectiveness of the proposed controller is validated through a simulation study conducted on a process system comprising integrated chemical reactors. The study highlights the controller’s ability to manage the interconnected dynamics of the system, ensuring stable and efficient operation under varying conditions.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106217"},"PeriodicalIF":5.4,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An active tool holder and robust LPV control design for practical vibration suppression in internal turning","authors":"Ziv Brand , Matthew O.T. Cole , Nikolay Razoronov","doi":"10.1016/j.conengprac.2024.106215","DOIUrl":"10.1016/j.conengprac.2024.106215","url":null,"abstract":"<div><div>This study presents a new system and control design for an active tool holder that can effectively suppress vibration and chatter in internal turning. The controller accounts for the influence of tool deflection during a preceding cut affecting the dynamics of the current cut, a key source of instability in machining processes. To deal with variability in dynamic behavior due to changing of the tool mounting conditions and overhang length, a robust H-infinity controller is synthesized based on a linear-parameter-varying (LPV) description of the machining dynamics. The parametric dependence allows the robustness levels and modal properties of the control system to be easily tuned in a workshop setting to achieve the best possible vibration reduction performance. The controller design accounts for the time-delayed feedback from cutting forces, and also the need to avoid spillover instability of unmodeled high frequency modes. The method is applied using a tool holder that integrates piezoelectric bending actuators and strain sensors in such a way that the overall size and shape of the tool is unaltered, thereby providing the functionality and ease of operation necessary for widespread adoption in manufacturing industries. Experiments conducted on a lathe machine demonstrate that root-mean-square vibration levels can be reduced by over 95% (and peak-to-peak values reduced by approximately 90%) in unstable cutting regimes, allowing high material removal rates with good surface finish. For stable cutting, the system can also reduce vibration by 10% to 50%, depending on cutting conditions.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106215"},"PeriodicalIF":5.4,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Constrained LPV control for collision avoidance using mixed steering and differential braking","authors":"Anh-Lam Do, François Fauvel","doi":"10.1016/j.conengprac.2024.106214","DOIUrl":"10.1016/j.conengprac.2024.106214","url":null,"abstract":"<div><div>This paper presents an LPV approach for mixed control of steering and differential braking of an automotive vehicle, under constraints. The mixed controller is used to improve the performance and robustness of the Advanced Evasive Steering system (an Active Safety ADAS) in emergency situations. First, the path-following problem is formulated in a generic LPV (Linear Parameter Varying) framework taking into account the vehicle speed and the actuators’ amplitude and rate constraints. Then, a simple and robust LPV state-feedback is optimized using LMI (Linear Matrix Inequality) technique. Experimental results obtained from various driving scenarios validate the effectiveness of this approach. Furthermore, the simplicity and low tuning effort required for implementing the proposed controller on conventional automotive Electronic Control Units (ECUs) make it highly advantageous for practical implementation.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106214"},"PeriodicalIF":5.4,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157051","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":"Hierarchical Deep Reinforcement Learning for cubesat guidance and control","authors":"Abdulla Tammam, Nabil Aouf","doi":"10.1016/j.conengprac.2024.106213","DOIUrl":"10.1016/j.conengprac.2024.106213","url":null,"abstract":"<div><div>Advancements in Reinforcement Learning (RL) algorithms and technologies have opened up new possibilities for their use in autonomous spacecraft control. This work presents a novel Hierarchical Deep Reinforcement Learning (HDRL) agent which can autonomously achieve satellite rendezvous while maintaining attitude control. The HDRL agents presented are built on a Hierarchical Actor–Critic (HAC) framework and are compared against combined and distributed TD3 RL agents. The controller has demonstrated the ability to achieve satellite rendezvous while performing large-angle slew manoeuvres with pointing accuracies of less than five degrees and resisting environmental perturbations. To assess the controller’s feasibility a six-Degree-of-Freedom (6-DoF) spacecraft dynamics testing platform was designed and constructed. The platform is made up of a reaction wheel actuated mock CubeSat, a frictionless space environment setup for attitude testing and a robotic arm based rendezvous mission simulator.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106213"},"PeriodicalIF":5.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158465","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":"Balancing production maximization and equipment degradation: Experimental application of a health-aware controller","authors":"José Matias, Johannes Jäschke","doi":"10.1016/j.conengprac.2024.106193","DOIUrl":"10.1016/j.conengprac.2024.106193","url":null,"abstract":"<div><div>This study implements a Health-Aware Controller (HAC) in an experimental rig that emulates an oil well system. The operational goal for the system is to maximize production, while ensuring that the degradation in each of the wells is controlled, such that no critical equipment breakdown happens before a planned maintenance stop. Health-aware control systems combine production optimization techniques with equipment health monitoring and they were recently proposed to systematically address the intuitive trade-off between optimizing production and minimizing equipment degradation. As such the controller is intended to maximize the system’s economic performance, while proactively preventing unexpected breakdowns. However, so far the concepts for health-aware control have been tested only in simulations. The main contribution of this paper is to implement and test a Health-Aware Controller on a physical system in lab conditions. Our experimental results confirm the <em>in-silico</em> findings on health-aware control that show that it is able to realize a balance between decreasing the equipment degradation and maximizing the system production, and has the potential to improve the system performance considering both revenues and maintenance costs. We further discuss several implementation aspects and highlight some implementation challenges that can be faced by other practitioners.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106193"},"PeriodicalIF":5.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jingxin Zhang , Min Wang , Xu Xu , Donghua Zhou , Xia Hong
{"title":"Adaptive monitoring for multimode nonstationary processes using cointegration analysis and probabilistic slow feature analysis","authors":"Jingxin Zhang , Min Wang , Xu Xu , Donghua Zhou , Xia Hong","doi":"10.1016/j.conengprac.2024.106209","DOIUrl":"10.1016/j.conengprac.2024.106209","url":null,"abstract":"<div><div>The condition monitoring of nonlinear, nonstationary and multimode processes is a difficult problem. Traditional multimode process monitoring methods generally assume that data from all potential modes are available, yet new modes may appear continuously in practice. This paper investigates an intelligent adaptive monitoring method for multimode nonstationary processes, which can deal with the appearance of new modes with ease. A comprehensive framework is proposed to decompose feature subspaces. First, long-term equilibrium features are extracted by adaptive cointegration analysis (ACA) to identify the mode, without using any prior mode information intelligently for online applications. Then, recursive attention probabilistic slow feature analysis integrated with elastic weight consolidation (RAttPSFA-EWC) is investigated to deal with the remaining dynamic information and extract dynamic and static slow features to maintain continual learning for multimodes. Once a new mode is detected automatically, the previously learned knowledge is consolidated while extracting new features, which is beneficial to enhancing the performance of similar modes. The proposed ACA-RAttPSFA-EWC acts as an online adaptive method by parameter updates with incoming normal data. Furthermore, several advanced methods are compared to demonstrate the strengths of ACA-RAttPSFA-EWC, and the proposed method is validated to be effective using a numerical case and a practical system.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106209"},"PeriodicalIF":5.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157825","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":"Design and validation of ADRC-based variable thrust control for a low-cost ethanol-oxygen rocket engine","authors":"Jingwei Xiong, Shang Liu, Hongbo Zhang","doi":"10.1016/j.conengprac.2024.106200","DOIUrl":"10.1016/j.conengprac.2024.106200","url":null,"abstract":"<div><div>A low-cost ethanol-oxygen rocket engine was developed for powered landing experiments in academic settings, utilizing 3D printing technology and off-the-shelf components, albeit with significant uncertainties and instabilities. To address these challenges, this study presents a continuous variable-thrust control strategy based on Active Disturbance Rejection Control (ADRC) theory, designed to regulate oxygen pressure. The oxygen pressure dynamics were modeled by analyzing the relationship between the valve opening angle and the ratio of the valve’s outlet to inlet pressure. Due to difficulties in deriving a precise physical model, the relative valve opening was introduced, enabling the use of a first-order transfer function for system representation. An ADRC controller was subsequently designed to modulate the valve opening angle to regulate the engine thrust. Modeling inaccuracies, time delays, and performance instabilities arising from low-cost components were mitigated using an Extended State Observer (ESO). To ensure safe and efficient parameter tuning, a Long Short-Term Memory (LSTM)-based method was employed, avoiding the risks associated with online optimization during ignition. The controller’s effectiveness was verified through cold gas and ignition experiments, demonstrating its ability to accurately track target pressures and adjust thrust, thereby confirming its feasibility for variable-thrust control systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106200"},"PeriodicalIF":5.4,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158456","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}
Wenkai Hu , Bin Hu , Yupeng Li , Peng Zhang , R. Bhushan Gopaluni , Weihua Cao
{"title":"Anomaly detection for drilling tools based on operating mode recognition and interval-augmented Mahalanobis distance","authors":"Wenkai Hu , Bin Hu , Yupeng Li , Peng Zhang , R. Bhushan Gopaluni , Weihua Cao","doi":"10.1016/j.conengprac.2024.106212","DOIUrl":"10.1016/j.conengprac.2024.106212","url":null,"abstract":"<div><div>Prompt and accurate anomaly detection of drilling tools is of great significance to ensure the safe and stable operation of drilling processes. However, the operating mode of a drilling tool may often change, leading to difficulties in distinguishing the drilling anomalies from the normal mode switching. Further, the variations of drilling signals caused by such anomalies in drilling tools are usually slight, making it quite challenging to separate the abnormal part from the normal part in the time series, which would compromise the accuracy and promptness of anomaly detection. Accordingly, this paper proposes a new method for anomaly detection of drilling tools based on operating mode recognition and interval-augmented Mahalanobis distance. The main contributions are threefold: 1) A mode recognition method based on the Earth Mover’s distance (EMD) and K-means clustering is proposed to identify drilling operating modes. 2) An anomaly detection method based on the interval-augmented Mahalanobis distance (IAMD) is proposed to detect anomalies of drilling tools. 3) An alarm generation strategy based on the kernel density estimation and alarm deadband is designed to reduce the false alarm rate. The effectiveness of the proposed method is demonstrated by industrial case studies involving a real drilling system.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106212"},"PeriodicalIF":5.4,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157827","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}
Yang Sun , Wenchao Xue , Jizhen Liu , Xiao Qi , Hui Deng
{"title":"Disturbance-exploitation based RMPC with application to multi-objective load frequency control in power systems","authors":"Yang Sun , Wenchao Xue , Jizhen Liu , Xiao Qi , Hui Deng","doi":"10.1016/j.conengprac.2024.106179","DOIUrl":"10.1016/j.conengprac.2024.106179","url":null,"abstract":"<div><div>This paper introduces a robust dual-model predictive control strategy for enhancing load frequency control in networked power systems. By seamlessly integrating a disturbance observer with a nonlinear model predictive control framework, our approach offers two main advantages: incorporating disturbance estimation into the optimization process and separately addressing robustness and performance. A nonlinear disturbance observer is developed to estimate drift from external power imbalances and unknown dynamics, updating the prediction model for accurate estimation. The dual-model nonlinear predictive control strategy is then introduced, ensuring input-to-state stability (ISS) to enhance frequency regulation and lower power generation costs. The performance of the proposed control method has been evaluated using the Speedgoat real-time simulator and compared with various control strategies under diverse scenarios. Experimental results indicate that the proposed method provides superior dynamic response and robust characteristics.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106179"},"PeriodicalIF":5.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158360","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}
Somayeh Jamshidi , Mehdi Mirzaei , Maria Khodaverdian , Paolo Castaldi
{"title":"Perturbation observer-based constrained fault tolerant control of flexible spacecraft using continuous predictive approach","authors":"Somayeh Jamshidi , Mehdi Mirzaei , Maria Khodaverdian , Paolo Castaldi","doi":"10.1016/j.conengprac.2024.106210","DOIUrl":"10.1016/j.conengprac.2024.106210","url":null,"abstract":"<div><div>This study presents a new constrained attitude control scheme for flexible spacecraft in the presence of system perturbations, including parametric uncertainties, external disturbances and actuator faults. In the proposed scheme, a baseline controller with increased robustness is firstly designed using an integral feedback-based continuous prediction approach to control the healthy spacecraft. At the same time, an extended state observer estimates the system perturbation. If the estimated perturbation exceeds a statistically predetermined threshold for aerodynamic/gravitational disturbances and the spacecraft’s parametric uncertainties, it may indicate a potential fault in the system. Upon detecting a fault, the controller transitions to a fault-tolerant mode, where the estimated perturbation is utilized to compensate for the faults and disturbances. Constrained stability is analyzed for both controllers using Lyapunov method. Also, hardware-in the-loop simulations have been conducted using a Raspberry Pi to highlight the real-world applicability of the proposed structure. The results show that different fault scenarios for the three reaction wheels can be accurately detected and compensated for using the perturbation observer information, all within a simple structure. The comparative results with active and passive fault-tolerant controllers demonstrate the higher efficiency of the proposed control system. Additionally, an extensive statistical analysis is performed using Monte Carlo simulations to show the robustness and reliability of the proposed system under uncertain conditions for spacecraft and disturbance parameters.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"156 ","pages":"Article 106210"},"PeriodicalIF":5.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158464","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}