Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185686
Martina Nobili, Camilla Fioravanti, S. Guarino, S. Ansaldi, M. Milazzo, P. Bragatto, R. Setola
A good cyber risk assessment is nowadays a matter of paramount importance for industrial systems and critical infrastructures. In a radical change and continuous development scenario such as that represented by Industry 4.0 plants, it is no longer sufficient to consider only static risks relating to the analysis of past data, but there is a need for a risk assessment that takes into account risks arising from emergent threats. In this paper, we propose a novel methodology for dynamic risk assessment that takes into account both the known values related to the static components of the system and the risks related to the emergence of new threats that have not yet been verified but are plausible according to experts. To achieve this, as part of the national “DRIVERS” project, an analysis of the most significant cyber-security factors was conducted to classify them in terms of relevance, considering both risk acceleration and risk mitigation aspects. This assessment is carried out by means of the multi-criteria decision support technique Analytic Hierarchy Process (AHP), performed by dividing the threat into a hierarchical structure.
{"title":"DRIVERS: A platform for dynamic risk assessment of emergent cyber threats for industrial control systems","authors":"Martina Nobili, Camilla Fioravanti, S. Guarino, S. Ansaldi, M. Milazzo, P. Bragatto, R. Setola","doi":"10.1109/MED59994.2023.10185686","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185686","url":null,"abstract":"A good cyber risk assessment is nowadays a matter of paramount importance for industrial systems and critical infrastructures. In a radical change and continuous development scenario such as that represented by Industry 4.0 plants, it is no longer sufficient to consider only static risks relating to the analysis of past data, but there is a need for a risk assessment that takes into account risks arising from emergent threats. In this paper, we propose a novel methodology for dynamic risk assessment that takes into account both the known values related to the static components of the system and the risks related to the emergence of new threats that have not yet been verified but are plausible according to experts. To achieve this, as part of the national “DRIVERS” project, an analysis of the most significant cyber-security factors was conducted to classify them in terms of relevance, considering both risk acceleration and risk mitigation aspects. This assessment is carried out by means of the multi-criteria decision support technique Analytic Hierarchy Process (AHP), performed by dividing the threat into a hierarchical structure.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115410491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185728
Parijat Prasun, Sunidhi Pandey, S. Kamal, Sandip Ghosh, Devender Singh
This article explores the theory of discrete-time gradient systems that converge in a finite amount of time and are governed by a difference equation with minima. Two algorithms with distinct structures are discussed, both aimed at achieving finite-time stabilization of these systems. These gradient-based algorithms have significant applications in solving optimization problems. Using the finite-time convergent techniques discussed in the article, a quadratic programming problem is solved, and an optimal solution is obtained within a finite time frame. The effectiveness of these proposed methods is demonstrated through simulation results.
{"title":"Discrete-Time Gradient Systems Governed by Difference Equation with Minima","authors":"Parijat Prasun, Sunidhi Pandey, S. Kamal, Sandip Ghosh, Devender Singh","doi":"10.1109/MED59994.2023.10185728","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185728","url":null,"abstract":"This article explores the theory of discrete-time gradient systems that converge in a finite amount of time and are governed by a difference equation with minima. Two algorithms with distinct structures are discussed, both aimed at achieving finite-time stabilization of these systems. These gradient-based algorithms have significant applications in solving optimization problems. Using the finite-time convergent techniques discussed in the article, a quadratic programming problem is solved, and an optimal solution is obtained within a finite time frame. The effectiveness of these proposed methods is demonstrated through simulation results.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116789956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185692
Jianlin Ye, S. Ioannou, Panagiota Nikolaou, M. Raspopoulos
This paper proposes a system architecture that uses deep learning image processing techniques to automatically identify forest fires in real-time using neural network models for small UAV applications. Considering the strict power and payload constraints of small UAVs, the proposed model runs on a compact, lightweight Raspberry Pi4B (RPi4B) and its performance is comparable to the state-of-the-art metrics (accuracy and real-time response) while achieving significant reduction in CPU usage and power consumption. The proposed YOLOv5 optimization approach used in this paper includes: 1) Replacing the backbone network to ShuffleNetV2, 2) Pruning the Head and Neck network following the backbone baseline, 3) Sparse training to implement the model-pruning method, 4) Fine-tuning of the pruned network to recover the detection accuracy and 5) Hardware acceleration by overclocking the RPi4B to improve the inference speed of the algorithm. Experimental results of the proposed forest fire detection system show that the proposed algorithm compared to the state-of-the-art that run on RPi single board computer, achieves 50% higher inference speed (9 FPS), reduction in CPU usage and temperature by 35% and 25% respectively and 10% reduced power consumption while the accuracy (92.5%) is only compromised by 2%. Finally, it is worth noting that the accuracy of the proposed algorithm is not affected by deviations in the bird-eye view angle.
{"title":"CNN based Real-time Forest Fire Detection System for Low-power Embedded Devices","authors":"Jianlin Ye, S. Ioannou, Panagiota Nikolaou, M. Raspopoulos","doi":"10.1109/MED59994.2023.10185692","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185692","url":null,"abstract":"This paper proposes a system architecture that uses deep learning image processing techniques to automatically identify forest fires in real-time using neural network models for small UAV applications. Considering the strict power and payload constraints of small UAVs, the proposed model runs on a compact, lightweight Raspberry Pi4B (RPi4B) and its performance is comparable to the state-of-the-art metrics (accuracy and real-time response) while achieving significant reduction in CPU usage and power consumption. The proposed YOLOv5 optimization approach used in this paper includes: 1) Replacing the backbone network to ShuffleNetV2, 2) Pruning the Head and Neck network following the backbone baseline, 3) Sparse training to implement the model-pruning method, 4) Fine-tuning of the pruned network to recover the detection accuracy and 5) Hardware acceleration by overclocking the RPi4B to improve the inference speed of the algorithm. Experimental results of the proposed forest fire detection system show that the proposed algorithm compared to the state-of-the-art that run on RPi single board computer, achieves 50% higher inference speed (9 FPS), reduction in CPU usage and temperature by 35% and 25% respectively and 10% reduced power consumption while the accuracy (92.5%) is only compromised by 2%. Finally, it is worth noting that the accuracy of the proposed algorithm is not affected by deviations in the bird-eye view angle.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125069716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185704
J. Wozniak
The problem of exact observability of a model of elastic-coupled strings is considered. The lack of regular exact observability is noted and required additional smoothness of observed signal is proposed.
{"title":"Exact Observability for a System of Coupled Wave Equations","authors":"J. Wozniak","doi":"10.1109/MED59994.2023.10185704","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185704","url":null,"abstract":"The problem of exact observability of a model of elastic-coupled strings is considered. The lack of regular exact observability is noted and required additional smoothness of observed signal is proposed.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126116925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185745
Antonios Porichis, Konstantinos Vasios, Myrto Iglezou, Vishwanathan Mohan, P. Chatzakos
Imitation Learning holds significant promise in enabling the automation of complex robotic manipulations tasks which are impossible to explicitly program. Mushroom harvesting is a task of high difficulty requiring weeks of intense training even for humans to master. In this work we present an end-to-end Imitation Learning pipeline that learns to apply the series of motions, namely reaching, grasping, twisting, and pulling the mushroom directly from pixel-level information. Mushroom harvesting experiments are carried out within a simulated environment that models the mushroom dynamics based on von Mises yielding theory with parameters obtained through expert picker demonstration wearing gloves with force sensors. We test the robustness of our technique by performing randomization on the camera extrinsic and intrinsic parameters as well as on the mushroom sizes. We also evaluate on different kinds of visual input namely grayscale and depth maps. Overall, our technique shows significant promise in automating mushroom harvesting directly from visual input while being remarkably lean in terms of computation intensity. Our models can be trained on a standard Laptop GPU in under one hour while inference of an action takes less than 1.5ms on a Laptop CPU. A brief overview of our experiments in video format is available at: https://bit.ly/41kCH7T
{"title":"Visual Imitation Learning for robotic fresh mushroom harvesting","authors":"Antonios Porichis, Konstantinos Vasios, Myrto Iglezou, Vishwanathan Mohan, P. Chatzakos","doi":"10.1109/MED59994.2023.10185745","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185745","url":null,"abstract":"Imitation Learning holds significant promise in enabling the automation of complex robotic manipulations tasks which are impossible to explicitly program. Mushroom harvesting is a task of high difficulty requiring weeks of intense training even for humans to master. In this work we present an end-to-end Imitation Learning pipeline that learns to apply the series of motions, namely reaching, grasping, twisting, and pulling the mushroom directly from pixel-level information. Mushroom harvesting experiments are carried out within a simulated environment that models the mushroom dynamics based on von Mises yielding theory with parameters obtained through expert picker demonstration wearing gloves with force sensors. We test the robustness of our technique by performing randomization on the camera extrinsic and intrinsic parameters as well as on the mushroom sizes. We also evaluate on different kinds of visual input namely grayscale and depth maps. Overall, our technique shows significant promise in automating mushroom harvesting directly from visual input while being remarkably lean in terms of computation intensity. Our models can be trained on a standard Laptop GPU in under one hour while inference of an action takes less than 1.5ms on a Laptop CPU. A brief overview of our experiments in video format is available at: https://bit.ly/41kCH7T","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123702855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185862
G. D. Carolis, Ryan K. Williams, A. Gasparri
This paper proposes a swarm-based approach for coordinating a multi-agent system (MAS) in a 3D environment to encircle a target for monitoring tasks in precision agriculture. Specifically, we are motivated by the objective of encircling large tree canopies in order to collaboratively gather information on tree health status. This goal is achieved by enhancing classical potential-based swarm design with a novel topology switching policy allowing the desired encirclement behavior to emerge. The resulting interaction protocol requires agents to utilize only local information, ensuring collision-free trajectories without restrictive assumptions on the undirected time-varying graph encoding the network topology. Numerical results are presented to demonstrate the effectiveness of the proposed approach.
{"title":"A Swarm-Based Distributed Algorithm for Target Encirclement with Application to Monitoring Tasks in Precision Agriculture Scenarios","authors":"G. D. Carolis, Ryan K. Williams, A. Gasparri","doi":"10.1109/MED59994.2023.10185862","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185862","url":null,"abstract":"This paper proposes a swarm-based approach for coordinating a multi-agent system (MAS) in a 3D environment to encircle a target for monitoring tasks in precision agriculture. Specifically, we are motivated by the objective of encircling large tree canopies in order to collaboratively gather information on tree health status. This goal is achieved by enhancing classical potential-based swarm design with a novel topology switching policy allowing the desired encirclement behavior to emerge. The resulting interaction protocol requires agents to utilize only local information, ensuring collision-free trajectories without restrictive assumptions on the undirected time-varying graph encoding the network topology. Numerical results are presented to demonstrate the effectiveness of the proposed approach.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"16 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114126733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185851
Mahmoud Abdulsalam, Zakaria Chekakta, N. Aouf, Maxwell Hogan
The application of robotic platforms for precision agriculture is gaining traction in modern research. However, the demand for a complete fruit dataset is still not satisfied. In this paper, we present fruity, a multi-modal fruit dataset with a variety of use cases such as 6D-pose estimation, fruit detection, fruit picking applications, etc. To the best of our knowledge, this dataset is the first-ever multi-modal fruit dataset tailored specifically for fruit 6D pose estimation in precision agriculture. The dataset is collected over a range of multiple sensors consisting of an RGB-D camera, thermal camera and an indoor tracking camera for ground truth poses. Fruity features RGB images, stereo depth images, thermal images, camera 6Dposes, fruit 6D-poses and relative 6D-poses between the cameras and fruits. The classes of the dataset are commonly harvested fruits which include: apples, oranges, bananas, avocados and lemons. It is also enriched with a clustered class to account for occlusion scenario. The dataset is recorded over multiple trajectories implemented with multiple platforms encompassing a robotic manipulator and an Unmanned Aerial Vehicle (UAV). The dataset alongside the documentation and utility tools is publicly available at: https://github.com/MahmoudYidi/Fruity.git.
{"title":"Fruity: A Multi-modal Dataset for Fruit Recognition and 6D-Pose Estimation in Precision Agriculture","authors":"Mahmoud Abdulsalam, Zakaria Chekakta, N. Aouf, Maxwell Hogan","doi":"10.1109/MED59994.2023.10185851","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185851","url":null,"abstract":"The application of robotic platforms for precision agriculture is gaining traction in modern research. However, the demand for a complete fruit dataset is still not satisfied. In this paper, we present fruity, a multi-modal fruit dataset with a variety of use cases such as 6D-pose estimation, fruit detection, fruit picking applications, etc. To the best of our knowledge, this dataset is the first-ever multi-modal fruit dataset tailored specifically for fruit 6D pose estimation in precision agriculture. The dataset is collected over a range of multiple sensors consisting of an RGB-D camera, thermal camera and an indoor tracking camera for ground truth poses. Fruity features RGB images, stereo depth images, thermal images, camera 6Dposes, fruit 6D-poses and relative 6D-poses between the cameras and fruits. The classes of the dataset are commonly harvested fruits which include: apples, oranges, bananas, avocados and lemons. It is also enriched with a clustered class to account for occlusion scenario. The dataset is recorded over multiple trajectories implemented with multiple platforms encompassing a robotic manipulator and an Unmanned Aerial Vehicle (UAV). The dataset alongside the documentation and utility tools is publicly available at: https://github.com/MahmoudYidi/Fruity.git.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114485296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185793
A. Leva, F. Terraneo, W. Fornaciari
The power of modern computing equipment, from small devices such as laptops through a variety of cases up to entire data centres, makes cooling vital. Especially in large-scale systems, delivering the right cooling to the right place at the right time is crucial for both computing performance and energy efficiency. As such, modern cooling systems require a lot of controls. Given the many cases to face, designing and assessing such controls requires tools to rapidly and modularly build and manage computationally efficient simulation models, sometimes concentrating on the thermal policies aboard on a chip, sometimes on the cooling of a rack, sometimes on an entire date centre with its fluid conditioning and transport machinery, and so forth. Though technology exist to address many such cases individually, a holistic approach to embrace them all within a unified modelling methodology and workflow is still the subject of research. In this paper we distil our experience over the last years, and discuss how a solution based on joining purpose-specific chip modelling (using the 3D-ICE simulator) and Equation-Based Object-Oriented Modelling (employing the Modelica language) can help the joint design of a computing system and its cooling.
{"title":"Efficient control-oriented modelling of heterogeneous large-scale computer cooling systems","authors":"A. Leva, F. Terraneo, W. Fornaciari","doi":"10.1109/MED59994.2023.10185793","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185793","url":null,"abstract":"The power of modern computing equipment, from small devices such as laptops through a variety of cases up to entire data centres, makes cooling vital. Especially in large-scale systems, delivering the right cooling to the right place at the right time is crucial for both computing performance and energy efficiency. As such, modern cooling systems require a lot of controls. Given the many cases to face, designing and assessing such controls requires tools to rapidly and modularly build and manage computationally efficient simulation models, sometimes concentrating on the thermal policies aboard on a chip, sometimes on the cooling of a rack, sometimes on an entire date centre with its fluid conditioning and transport machinery, and so forth. Though technology exist to address many such cases individually, a holistic approach to embrace them all within a unified modelling methodology and workflow is still the subject of research. In this paper we distil our experience over the last years, and discuss how a solution based on joining purpose-specific chip modelling (using the 3D-ICE simulator) and Equation-Based Object-Oriented Modelling (employing the Modelica language) can help the joint design of a computing system and its cooling.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124589562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185762
Aliki Stefanopoulou, S. Gkelios, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos, Y. Boutalis
In this study we propose a model-based dynamic path planning algorithm that is designed to navigate Autonomous Vehicles through complex and dynamic environments. To achieve that, a novel spline-based approach is utilized for the production of several candidate paths along a predetermined route and a Gaussian-based function is utilized for their evaluation. Our algorithm takes into account various factors, such as static and dynamic objects, to make the appropriate decisions for the vehicle’s path, making it a promising solution for such objects during an autonomous vehicle navigation. The algorithm was tested in high-fidelity scenarios using CARLA Simulator, which is a powerful tool for simulating autonomous vehicle scenarios. The results indicate that the proposed algorithm is capable of generating efficient and safe paths for the vehicle to follow.
{"title":"Spline-Based Dynamic Object Handling in Autonomous Vehicles: A Model-Based Path Planning Algorithm","authors":"Aliki Stefanopoulou, S. Gkelios, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos, Y. Boutalis","doi":"10.1109/MED59994.2023.10185762","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185762","url":null,"abstract":"In this study we propose a model-based dynamic path planning algorithm that is designed to navigate Autonomous Vehicles through complex and dynamic environments. To achieve that, a novel spline-based approach is utilized for the production of several candidate paths along a predetermined route and a Gaussian-based function is utilized for their evaluation. Our algorithm takes into account various factors, such as static and dynamic objects, to make the appropriate decisions for the vehicle’s path, making it a promising solution for such objects during an autonomous vehicle navigation. The algorithm was tested in high-fidelity scenarios using CARLA Simulator, which is a powerful tool for simulating autonomous vehicle scenarios. The results indicate that the proposed algorithm is capable of generating efficient and safe paths for the vehicle to follow.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"6 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129129832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185891
Valeria Bonagura, Chiara Foglietta, S. Panzieri, F. Pascucci
Large systems are typically partitioned into many subsystems to reduce computational load. For this reason, the Interlaced Extended Kalman Filter (IEKF) was created, in which each subsystem estimates only its own state while utilizing information from other subsystems. The information shared is normally the a-priori and a-posteriori state, as well as the a-priori and a-posteriori covariance matrix.Subsystems, however, cannot, for technological reasons, always operate at the same rate. To address this issue, we propose a multirate distributed filter, in which the subsystems operate independently and only share information when a novel measurement activates each subsystem. The only information exchanged is the a-posteriori state and covariance matrix. In the paper, we demonstrate that the proposed filtering technique is accurate and effective by examining the convergence property.A water tank case study is detailed, and two subsystems with different but fixed rates are discussed, illustrating the efficiency of the proposed solution. The same approach can be modified to take into account numerous instances of subsystems as well as missing data due to an unreliable communication route.
{"title":"Multirate Interlaced Kalman Filter","authors":"Valeria Bonagura, Chiara Foglietta, S. Panzieri, F. Pascucci","doi":"10.1109/MED59994.2023.10185891","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185891","url":null,"abstract":"Large systems are typically partitioned into many subsystems to reduce computational load. For this reason, the Interlaced Extended Kalman Filter (IEKF) was created, in which each subsystem estimates only its own state while utilizing information from other subsystems. The information shared is normally the a-priori and a-posteriori state, as well as the a-priori and a-posteriori covariance matrix.Subsystems, however, cannot, for technological reasons, always operate at the same rate. To address this issue, we propose a multirate distributed filter, in which the subsystems operate independently and only share information when a novel measurement activates each subsystem. The only information exchanged is the a-posteriori state and covariance matrix. In the paper, we demonstrate that the proposed filtering technique is accurate and effective by examining the convergence property.A water tank case study is detailed, and two subsystems with different but fixed rates are discussed, illustrating the efficiency of the proposed solution. The same approach can be modified to take into account numerous instances of subsystems as well as missing data due to an unreliable communication route.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121462118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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