Faizan Mehmood , Lenos Hadjidemetriou , Panayiotis M. Papadopoulos , Marios M. Polycarpou
{"title":"Synergistic frameworks for sensor fault isolation and accommodation in grid-side converters","authors":"Faizan Mehmood , Lenos Hadjidemetriou , Panayiotis M. Papadopoulos , Marios M. Polycarpou","doi":"10.1016/j.jai.2024.09.001","DOIUrl":"10.1016/j.jai.2024.09.001","url":null,"abstract":"<div><div>The stable and reliable operation of grid-integrated renewable energy systems requires advanced control and coordination of grid-side converters (GSCs), utilizing the feedback measurements of voltage and current sensors from both the direct current (DC) and alternating current (AC) sides of the converter. However, the effective operation of the converter is susceptible to sensor failures or divergence from their proper operation. Although sensor fault detection algorithms are usually effective under abrupt faults, the fault propagation effect caused by the physical interconnection between the DC and AC sides of the converter may limit the performance of the sensor fault isolation process in revealing the exact location of a potential faulty sensor. Therefore, this work proposes a robust, model-based fault isolation and accommodation scheme. Specifically, a synergistic sensor fault isolation framework based on adaptive estimation schemes is proposed for both single and multiple faults in the DC voltage and AC current sensors, considering modeling uncertainty and measurement noise. The performance analysis in terms of stability, learning capability, and fault isolability is rigorously examined. An accommodation scheme based on a virtual sensor utilizing dynamic sensor fault estimation with real-time learning capabilities is applied to a GSC. Finally, the performance of the proposed fault isolation and accommodation scheme is evaluated through simulation analysis under several scenarios involving single and multiple sensor faults.</div></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 4","pages":"Pages 202-218"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143142844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xinhang Xu , Yizhuo Yang , Muqing Cao, Thien-Minh Nguyen, Kun Cao, Lihua Xie
{"title":"A data-driven control method for ground locomotion on sloped terrain of a hybrid aerial-ground robot","authors":"Xinhang Xu , Yizhuo Yang , Muqing Cao, Thien-Minh Nguyen, Kun Cao, Lihua Xie","doi":"10.1016/j.jai.2024.08.001","DOIUrl":"10.1016/j.jai.2024.08.001","url":null,"abstract":"<div><div>In this work, we present a data-driven solution for the attitude control of DoubleBee on slopes. DoubleBee is a novel hybrid aerial-ground robot with two rotors and two active wheels. Inspired by the physics modeling of the system, we add a channel-separated attention head to a deep ReLU neural network to predict disturbances from ground effects, motor torques and rotation axis shift. The proposed neural network is Lipschitz continuous, has fewer parameters and performs better for disturbance estimation than the baseline deep ReLU neural network. Then, we design a sliding mode controller using these predictions and establish its input-to-state stability and error bounds. Experiments show improvements of the proposed neural network in training speed and robustness over a baseline ReLU network, and a 40% reduction in tracking error compared to a baseline PID controller.</div></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 4","pages":"Pages 219-229"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kunjie Yu , Jintao Lian , Ying Bi , Jing Liang , Bing Xue , Mengjie Zhang
{"title":"A genetic programming approach with adaptive region detection to skin cancer image classification","authors":"Kunjie Yu , Jintao Lian , Ying Bi , Jing Liang , Bing Xue , Mengjie Zhang","doi":"10.1016/j.jai.2024.08.003","DOIUrl":"10.1016/j.jai.2024.08.003","url":null,"abstract":"<div><div>Dermatologists typically require extensive experience to accurately classify skin cancer. In recent years, the development of computer vision and machine learning has provided new methods for assisted diagnosis. Existing skin cancer image classification methods have certain limitations, such as poor interpretability, the requirement of domain knowledge for feature extraction, and the neglect of lesion area information in skin images. This paper proposes a new genetic programming (GP) approach to automatically learn global and/or local features from skin images for classification. To achieve this, a new function set and a new terminal set have been developed. The proposed GP method can automatically and flexibly extract effective local/global features from different types of input images, thus providing a comprehensive description of skin images. A new region detection function has been developed to select the lesion areas from skin images for feature extraction. The performance of this approach is evaluated on three skin cancer image classification tasks, and compared with three GP methods and six non-GP methods. The experimental results show that the new approach achieves significantly better or similar performance in most cases. Further analysis validates the effectiveness of our parameter settings, visualizes the multiple region detection functions used in the individual evolved by the proposed approach, and demonstrates its good convergence ability.</div></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 4","pages":"Pages 240-249"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143142846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiakang Zhou , Yue Cao , Yu-Xuan Ren , Steve Feng Shu
{"title":"SPADE: A spatial information assisted collision distance estimator for robotic arm","authors":"Jiakang Zhou , Yue Cao , Yu-Xuan Ren , Steve Feng Shu","doi":"10.1016/j.jai.2024.11.001","DOIUrl":"10.1016/j.jai.2024.11.001","url":null,"abstract":"<div><div>The movement of a robotic arm in the working environment requires efficient and adequate motion planning. The procedure of collision detection based on the object geometry is crucial to plan the motion trajectories, and usually requires intensive resource and considerable time. Many learning-based collision detection schemes have been developed to improve the efficiency of collision detection. However, current learning-based collision detection methods are either not accurate enough or prone to low efficiency. We propose a simple, yet highly accurate collision distance estimator, a spatial information assisted distance estimator, i.e., SPADE, in which spatial information of both robotic arms and obstacles are encoded by multiple encoders. With evaluation in both static and dynamic environments, our model shows higher prediction accuracy than multiple baselines, and higher accuracy can be corroborated by experiment with our model under the premise of equal inference efficiency. In addition, our model shows better robustness than baseline in real-world path planning.</div></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 4","pages":"Pages 250-259"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143142847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive neural network event-triggered secure formation control of nonholonomic mobile robots subject to deception attacks","authors":"Kai Wang , Wei Wu , Shaocheng Tong","doi":"10.1016/j.jai.2024.10.002","DOIUrl":"10.1016/j.jai.2024.10.002","url":null,"abstract":"<div><div>This paper investigates the adaptive neural network (NN) event-triggered secure formation control problem for nonholonomic mobile robots (NMRs) subject to deception attacks. The NNs are employed to approximate unknown nonlinear functions in robotic dynamics. Since the transmission channel from sensor-to-controller is vulnerable to deception attacks, a NN estimation technique is introduced to estimate the unknown deception attacks. In order to alleviate the amount of communication between controller-and-actuator, an event-triggered mechanism with relative threshold strategy is established. Then, an adaptive NN event-triggered secure formation control method is proposed. It is proved that all closed-loop signals of controlled systems are bounded and the formation tracking errors converge a neighborhood of the origin in the presence of deception attacks. The comparative simulations illustrate the effectiveness of the proposed secure formation control scheme.</div></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 4","pages":"Pages 260-268"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143143756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast and robust strain signal processing for aircraft structural health monitoring","authors":"Cong Wang , Xin Tan , Xiaobin Ren , Xuelong Li","doi":"10.1016/j.jai.2024.07.001","DOIUrl":"10.1016/j.jai.2024.07.001","url":null,"abstract":"<div><p>This work elaborates a fast and robust structural health monitoring scheme for copying with aircraft structural fatigue. The type of noise in structural strain signals is determined by using a statistical analysis method, which can be regarded as a mixture of Gaussian-like (tiny hairy signals) and impulse-like noise (single signals with anomalous movements in peak and valley areas). Based on this, a least squares filtering method is employed to preprocess strain signals. To precisely eliminate noise or outliers in strain signals, we propose a novel variational model to generate step signals instead of strain ones. Expert judgments are employed to classify the generated signals. Based on the classification labels, whether the aircraft is structurally healthy is accurately judged. By taking the generated step count vectors and labels as an input, a discriminative neural network is proposed to realize automatic signal discrimination. The network output means whether the aircraft structure is healthy or not. Experimental results demonstrate that the proposed scheme is effective and efficient, as well as achieves more satisfactory results than other peers.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 160-168"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000297/pdfft?md5=c3b2f08b402beb05f4d355921b723cb4&pid=1-s2.0-S2949855424000297-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141690455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prescribed finite-time stabilization of fuzzy neural networks with time-varying controller","authors":"Yufeng Zhou, Yawen Zhou, Peng Wan","doi":"10.1016/j.jai.2024.07.003","DOIUrl":"10.1016/j.jai.2024.07.003","url":null,"abstract":"<div><p>This paper investigates the exponential and prescribed finite-time stabilization with time-varying controller. First, the constraints of boundedness and differentiability on time delays are simultaneously relaxed, the Lipschitz condition for activation function is also relaxed. Second, different from the traditional Lyapunov function, two different time-varying Lyapunov functions are respectively constructed to achieve the exponential and prescribed finite-time stabilization. Significantly, the exponential convergence rate and the settling time are constants that can be given in advance and are not affected by system parameters and initial states. In addition, the time-varying controllers have good tolerance for disturbance caused by discontinuous functions and the disturbance is perfectly resolved and does not affect the control performance. Especially, the form of controllers is relatively simple and there is not necessary to design the fractional-order controllers for prescribed finite-time stabilization. Furthermore, the exponential and prescribed finite-time stabilization for FNNs without delay are respectively established via continuous time-varying state feedback control. Finally, examples show the effectiveness of the proposed control methods.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 176-184"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000315/pdfft?md5=1f477ba1b94b230df31209cb37a43f67&pid=1-s2.0-S2949855424000315-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141693695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"AV-FDTI: Audio-visual fusion for drone threat identification","authors":"Yizhuo Yang, Shenghai Yuan, Jianfei Yang, Thien Hoang Nguyen, Muqing Cao, Thien-Minh Nguyen, Han Wang, Lihua Xie","doi":"10.1016/j.jai.2024.06.002","DOIUrl":"10.1016/j.jai.2024.06.002","url":null,"abstract":"<div><p>In response to the evolving challenges posed by small unmanned aerial vehicles (UAVs), which have the potential to transport harmful payloads or cause significant damage, we present AV-FDTI, an innovative Audio-Visual Fusion system designed for Drone Threat Identification. AV-FDTI leverages the fusion of audio and omnidirectional camera feature inputs, providing a comprehensive solution to enhance the precision and resilience of drone classification and 3D localization. Specifically, AV-FDTI employs a CRNN network to capture vital temporal dynamics within the audio domain and utilizes a pretrained ResNet50 model for image feature extraction. Furthermore, we adopt a visual information entropy and cross-attention-based mechanism to enhance the fusion of visual and audio data. Notably, our system is trained based on automated Leica tracking annotations, offering accurate ground truth data with millimeter-level accuracy. Comprehensive comparative evaluations demonstrate the superiority of our solution over the existing systems. In our commitment to advancing this field, we will release this work as open-source code and wearable AV-FDTI design, contributing valuable resources to the research community.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 144-151"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000285/pdfft?md5=684e37e58a4ae5abf55addf8f81639b9&pid=1-s2.0-S2949855424000285-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal decarbonisation pathway for mining truck fleets","authors":"","doi":"10.1016/j.jai.2024.03.003","DOIUrl":"10.1016/j.jai.2024.03.003","url":null,"abstract":"<div><p>The fossil fuel powered mining truck fleets can contribute up to 80% of total emissions in open pit mines. This study investigates the optimal decarbonisation pathway for mining truck fleets. Notably, our proposed pathway incorporates power generation, negative carbon technologies, and carbon trading. Technical, financial, and environmental models of decarbonisation technologies are established, capturing regional variations and time dynamic characteristics such as cost trends and carbon capture efficiency. The dynamic natures of characteristics pose challenges for using the cost-effective analyses approach to find the optimal decarbonisation pathway. To address this, we introduce a mixed-integer programming optimisation framework to find the decarbonisation pathway with minimum life cycle costs during the planning period. A case study for the optimal decarbonisation pathway of truck fleets in a South African coal mine is conducted to illustrate the applicability of the proposed model. Results indicate that the optimal decarbonisation pathway is significantly influenced by factors such as land cost, annual budget, and carbon trading prices. The proposed method provides invaluable guidance for transitioning towards a cleaner and more sustainable mining industry.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 129-143"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000170/pdfft?md5=4f517fd6eea714a6a50b1922abb059fc&pid=1-s2.0-S2949855424000170-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140270581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Containment control of heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded delays","authors":"","doi":"10.1016/j.jai.2024.06.001","DOIUrl":"10.1016/j.jai.2024.06.001","url":null,"abstract":"<div><p>This paper addresses the problem of containment control for heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded communication delays. The objective is to design a distributed control strategy that ensures the output of each follower converges to the convex hull formed by the outputs of a group of leaders in mean square sense. A novel distributed observer is proposed by tackling both Markovian randomly switching topologies and unbounded delays. Then, a distributed state feedback controller and a distributed output feedback controller are developed based on the distributed observer, respectively. Finally, simulation results are provided to demonstrate the effectiveness of the proposed controllers.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 152-159"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000200/pdfft?md5=fa95492a4e0134ae81c991866c07465c&pid=1-s2.0-S2949855424000200-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141406216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}