Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185748
Andreea Bianca Popescu, C. Nita, Ioana Antonia Taca, A. Vizitiu, L. Itu
Deep learning (DL)-based solutions have been extensively researched in the medical domain in recent years, enhancing the efficacy of diagnosis, planning, and treatment. Since the usage of health-related data is strictly regulated, processing medical records outside the hospital environment for developing and using DL models demands robust data protection measures. At the same time, it can be challenging to guarantee that a DL solution delivers a minimum level of performance when being trained on secured data, without being specifically designed for the given task. Our approach uses singular value decomposition (SVD) and principal component analysis (PCA) to obfuscate the medical images before employing them in the DL analysis. The capability of DL algorithms to extract relevant information from secured data is assessed on a task of angiographic view classification based on obfuscated frames. The security level is probed by simulated artificial intelligence (AI)-based reconstruction attacks, considering two threat actors with different prior knowledge of the targeted data. The degree of privacy is quantitatively measured using similarity indices. Although a trade-off between privacy and accuracy should be considered, the proposed technique allows for training the angiographic view classifier exclusively on secured data with satisfactory performance and with no computational overhead, model adaptation, or hyperparameter tuning. While the obfuscated medical image content is well protected against human perception, the hypothetical reconstruction attack proved that it is also difficult to recover the complete information of the original frames.
{"title":"Privacy-Preserving Medical Image Classification through Deep Learning and Matrix Decomposition","authors":"Andreea Bianca Popescu, C. Nita, Ioana Antonia Taca, A. Vizitiu, L. Itu","doi":"10.1109/MED59994.2023.10185748","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185748","url":null,"abstract":"Deep learning (DL)-based solutions have been extensively researched in the medical domain in recent years, enhancing the efficacy of diagnosis, planning, and treatment. Since the usage of health-related data is strictly regulated, processing medical records outside the hospital environment for developing and using DL models demands robust data protection measures. At the same time, it can be challenging to guarantee that a DL solution delivers a minimum level of performance when being trained on secured data, without being specifically designed for the given task. Our approach uses singular value decomposition (SVD) and principal component analysis (PCA) to obfuscate the medical images before employing them in the DL analysis. The capability of DL algorithms to extract relevant information from secured data is assessed on a task of angiographic view classification based on obfuscated frames. The security level is probed by simulated artificial intelligence (AI)-based reconstruction attacks, considering two threat actors with different prior knowledge of the targeted data. The degree of privacy is quantitatively measured using similarity indices. Although a trade-off between privacy and accuracy should be considered, the proposed technique allows for training the angiographic view classifier exclusively on secured data with satisfactory performance and with no computational overhead, model adaptation, or hyperparameter tuning. While the obfuscated medical image content is well protected against human perception, the hypothetical reconstruction attack proved that it is also difficult to recover the complete information of the original frames.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"193 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":"124298163","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/MED59994.2023.10185723
Federica Galli, V. Sircoulomb, Giuseppe Fiore, G. Hoblos, Philippe Weber
Rolling Element Bearings (REB) are one of the key components of rotating machinery. Their correct functioning and failure have been the object of many studies and today many models are available that can reproduce their vibration response. Most of them are applied for diagnosis purposes and simulate the bearing behaviour in steady state considering fixed surface defect. Such vibration signals are useful to perform bearing diagnosis but they lack the necessary information for predictive algorithms conceived for prognosis applications. The objective of the work presented here is using an already existing dynamic model to simulate vibration signals under unsteady degradation conditions. Different degradation profiles have been proposed to simulate the evolution of local surface defects on the bearing components to form a synthetic database for future prognosis applications. The obtained signals can be very useful for data-drive prognosis algorithm training. As proof, they were used for RUL (Remaining Useful Life) estimation with a simple approach and proved to be effective.
{"title":"Dynamic modelling for non-stationary bearing vibration signals","authors":"Federica Galli, V. Sircoulomb, Giuseppe Fiore, G. Hoblos, Philippe Weber","doi":"10.1109/MED59994.2023.10185723","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185723","url":null,"abstract":"Rolling Element Bearings (REB) are one of the key components of rotating machinery. Their correct functioning and failure have been the object of many studies and today many models are available that can reproduce their vibration response. Most of them are applied for diagnosis purposes and simulate the bearing behaviour in steady state considering fixed surface defect. Such vibration signals are useful to perform bearing diagnosis but they lack the necessary information for predictive algorithms conceived for prognosis applications. The objective of the work presented here is using an already existing dynamic model to simulate vibration signals under unsteady degradation conditions. Different degradation profiles have been proposed to simulate the evolution of local surface defects on the bearing components to form a synthetic database for future prognosis applications. The obtained signals can be very useful for data-drive prognosis algorithm training. As proof, they were used for RUL (Remaining Useful Life) estimation with a simple approach and proved to be effective.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"163 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120934132","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/MED59994.2023.10185784
Nguyen Ba Huy, Anh Phuong Hoang, Van Quy Phung
The paper proposes a method for synthesizing the control of linear plants with a guarantee of finding the controlled variable in a given set under the condition that only the system output is measurable. In this work, the output feedback control is not used because of its complexity of synthesis, but the observer-based control using the Luenberger observer is used. A change of coordinates is applied to transfer the original problem with output constraints to a problem of control by an auxiliary variable without constraints. The controller’s adjustable parameter is selected from the solution of linear matrix inequalities, which enhances the practical applicability of the proposed method. Numerical simulations using Matlab confirm the effectiveness of the proposed method by demonstrating the boundedness of all signals in the control system and the presence of controlled signals within the given set.
{"title":"Observer-based control MIMO linear systems with providing output in given set","authors":"Nguyen Ba Huy, Anh Phuong Hoang, Van Quy Phung","doi":"10.1109/MED59994.2023.10185784","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185784","url":null,"abstract":"The paper proposes a method for synthesizing the control of linear plants with a guarantee of finding the controlled variable in a given set under the condition that only the system output is measurable. In this work, the output feedback control is not used because of its complexity of synthesis, but the observer-based control using the Luenberger observer is used. A change of coordinates is applied to transfer the original problem with output constraints to a problem of control by an auxiliary variable without constraints. The controller’s adjustable parameter is selected from the solution of linear matrix inequalities, which enhances the practical applicability of the proposed method. Numerical simulations using Matlab confirm the effectiveness of the proposed method by demonstrating the boundedness of all signals in the control system and the presence of controlled signals within the given set.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"95 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":"124047845","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/MED59994.2023.10185875
Seyed Mohsen Hosseini, Marco Frego, Angelika Peer
In recent years, the global wood products market has become highly competitive. Due to this, sawmills seek to improve their efficiency throughout their production process. In this regard, improving sawing efficiency through improved cutting strategies is vital for preventing overproduction and waste issues. In this paper, we deal with the sawing optimization problem defined as the problem of cutting rectangular boards from cylindrical logs with circular cross sections. In particular, we consider a sawing pattern that is highly beneficial for wood manufacturing, namely cant sawing. We take into account feasibility, capacity, non-overlapping, and technical constraints of the sawing process. We first develop an exact model of this combinatorial optimization problem as a mixed-integer nonlinear programming (MINLP) problem. However, this exact model involves a high level of combinatorics and requires considerable computation time, becoming computationally intractable as the problem size increases. To deal with this challenge, we develop a constructive heuristic approach, namely strip-bottom-left-fill (SBLF) heuristic, that builds a feasible cutting according to a list of ordered rectangles and a set of placement policies. The simulation results confirm the superiority of our proposed approach over the MINLP model and a state-of-the-art heuristic approach in terms of computational effort as well as memory and search requirements while preserving cutting yield efficiency
{"title":"Cutting Unequal Rectangular Boards from Cylindrical Logs in Wood Products Manufacturing: A Heuristic Approach","authors":"Seyed Mohsen Hosseini, Marco Frego, Angelika Peer","doi":"10.1109/MED59994.2023.10185875","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185875","url":null,"abstract":"In recent years, the global wood products market has become highly competitive. Due to this, sawmills seek to improve their efficiency throughout their production process. In this regard, improving sawing efficiency through improved cutting strategies is vital for preventing overproduction and waste issues. In this paper, we deal with the sawing optimization problem defined as the problem of cutting rectangular boards from cylindrical logs with circular cross sections. In particular, we consider a sawing pattern that is highly beneficial for wood manufacturing, namely cant sawing. We take into account feasibility, capacity, non-overlapping, and technical constraints of the sawing process. We first develop an exact model of this combinatorial optimization problem as a mixed-integer nonlinear programming (MINLP) problem. However, this exact model involves a high level of combinatorics and requires considerable computation time, becoming computationally intractable as the problem size increases. To deal with this challenge, we develop a constructive heuristic approach, namely strip-bottom-left-fill (SBLF) heuristic, that builds a feasible cutting according to a list of ordered rectangles and a set of placement policies. The simulation results confirm the superiority of our proposed approach over the MINLP model and a state-of-the-art heuristic approach in terms of computational effort as well as memory and search requirements while preserving cutting yield efficiency","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"9 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":"117100733","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/MED59994.2023.10185883
M. Khlebnikov, A. Tremba
An approach to the solution of a robust sparse filtering problem via use of a reduced number of outputs under arbitrary bounded external disturbances and norm-bounded system uncertainties using an observer is proposed. The approach is based on the LMI technique and the method of invariant ellipsoids, and made it possible to reduce the initial problem to parameterized semidefinite programming that can be easily solved numerically. Two ways to control sparsity are proposed: controlled relaxation approach and Pareto frontier approach.
{"title":"Robust Sparse Filtering Under Bounded Exogenous Disturbances","authors":"M. Khlebnikov, A. Tremba","doi":"10.1109/MED59994.2023.10185883","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185883","url":null,"abstract":"An approach to the solution of a robust sparse filtering problem via use of a reduced number of outputs under arbitrary bounded external disturbances and norm-bounded system uncertainties using an observer is proposed. The approach is based on the LMI technique and the method of invariant ellipsoids, and made it possible to reduce the initial problem to parameterized semidefinite programming that can be easily solved numerically. Two ways to control sparsity are proposed: controlled relaxation approach and Pareto frontier approach.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"262 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":"131519624","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/MED59994.2023.10185699
Nikolas Sacchi, Edoardo Vacchini, A. Ferrara
In this paper, we propose a novel neural network based state constrained integral sliding mode (NN-SCISM) control algorithm for nonlinear system with partially unknown dynamics in presence of time-varying constraints. In particular, the drift term characterizing the system dynamics is estimated by using a two-layer neural network, whose weights are adjusted according to adaptation laws designed relying on stability analysis. Thanks to a sliding variable which varies depending on the minimum distance between the system state and the current closest constraint, the control algorithm is able to drive the system state to a desired target state, while avoiding the forbidden states contained in the time-varying set delimited by the constraints. The proposal has been theoretical analysed and assessed in simulation.
{"title":"Neural network based integral sliding mode control of systems with time-varying state constraints","authors":"Nikolas Sacchi, Edoardo Vacchini, A. Ferrara","doi":"10.1109/MED59994.2023.10185699","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185699","url":null,"abstract":"In this paper, we propose a novel neural network based state constrained integral sliding mode (NN-SCISM) control algorithm for nonlinear system with partially unknown dynamics in presence of time-varying constraints. In particular, the drift term characterizing the system dynamics is estimated by using a two-layer neural network, whose weights are adjusted according to adaptation laws designed relying on stability analysis. Thanks to a sliding variable which varies depending on the minimum distance between the system state and the current closest constraint, the control algorithm is able to drive the system state to a desired target state, while avoiding the forbidden states contained in the time-varying set delimited by the constraints. The proposal has been theoretical analysed and assessed in simulation.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"106 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":"131628131","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/MED59994.2023.10185839
Kirill Matveev, D. Bazylev, D. Dobriborsci
In this paper, we consider the problem of flux, position and speed observer design for permanent magnet synchronous motors (PMSMs) with uncertain parameters. It is assumed that the only measured signals are stator currents and control voltages. The key feature of the proposed approach is that it requires the knowledge of only one structural parameter of PMSM model – the number of pole pairs. Thus, all electrical and mechanical parameters, namely, the stator resistance and inductance, constant flux from permanent magnets, motor inertia and viscous friction coefficient are assumed to be unknown. A new nonlinear parameterization of motor model is proposed that is resulted in the regression model of eleven unknown parameters including the stator resistance and inductance as well as two parameters involved in the state observer design. The dynamic regressor extension and mixing (DREM) estimator is used to provide good performance and fast estimation of unknown parameters which is more efficient than the standard gradient approach in the case of high-dimensional regression models. Simulation results carried out for a typical scenario of motor operation illustrate good performance of the designed observer and parameter estimators.
{"title":"Position and Speed Observer for PMSM with Unknown Stator Resistance and Inductance","authors":"Kirill Matveev, D. Bazylev, D. Dobriborsci","doi":"10.1109/MED59994.2023.10185839","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185839","url":null,"abstract":"In this paper, we consider the problem of flux, position and speed observer design for permanent magnet synchronous motors (PMSMs) with uncertain parameters. It is assumed that the only measured signals are stator currents and control voltages. The key feature of the proposed approach is that it requires the knowledge of only one structural parameter of PMSM model – the number of pole pairs. Thus, all electrical and mechanical parameters, namely, the stator resistance and inductance, constant flux from permanent magnets, motor inertia and viscous friction coefficient are assumed to be unknown. A new nonlinear parameterization of motor model is proposed that is resulted in the regression model of eleven unknown parameters including the stator resistance and inductance as well as two parameters involved in the state observer design. The dynamic regressor extension and mixing (DREM) estimator is used to provide good performance and fast estimation of unknown parameters which is more efficient than the standard gradient approach in the case of high-dimensional regression models. Simulation results carried out for a typical scenario of motor operation illustrate good performance of the designed observer and parameter estimators.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"23 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":"124211431","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/MED59994.2023.10185678
K. V. Sklyar, S. Ignatovich, G. Sklyar
We consider nonlinear multi-input non-autonomous control systems and analyze their invariants analogous to those introduced in Sklyar K. On mappability of control systems to linear systems with analytic matrices. Systems Control Lett. 134 (2019) 104572. We show that, compared to single-input systems, new invariants should be introduced. We give a complete set of invariants for one subclass of multi-input non-autonomous systems and propose a method of solving the time-optimal problem for such systems.
{"title":"Linearizability problem and invariants for multi-input non-autonomous control systems","authors":"K. V. Sklyar, S. Ignatovich, G. Sklyar","doi":"10.1109/MED59994.2023.10185678","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185678","url":null,"abstract":"We consider nonlinear multi-input non-autonomous control systems and analyze their invariants analogous to those introduced in Sklyar K. On mappability of control systems to linear systems with analytic matrices. Systems Control Lett. 134 (2019) 104572. We show that, compared to single-input systems, new invariants should be introduced. We give a complete set of invariants for one subclass of multi-input non-autonomous systems and propose a method of solving the time-optimal problem for such systems.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"14 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":"115034234","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/MED59994.2023.10185669
Mike Anastasiadis, K. Moschou, Kristina Livitckaia, K. Votis, D. Tzovaras
Along with the evolution of communication technologies, cybersecurity has evolved, and so have its new directions and demands. There is a wide range of tools to detect, analyse, or protect systems from malicious activity. Yet, as new technologies are emerging and maturing, the need for particular domain solutions arises. This paper proposes a methodology for a honeypot network organisation mimicking vital autonomous vehicle sensors inside the Internet of Vehicles (IoV) infrastructure, along with attack propagation patterns analysis based on the logs collected from the honeypots. The discovery of sequential patterns is based on Markov Chain models applied in the honey-farm data. Further, these trained models are applied with graph-based algorithms to discover the interaction patterns between honeypots targeting the discovery of segments that were attacked in series. The intelligence produced from the analysis is used to rank and estimate the relative importance of the honeypots in their framework. The results of our study allowed us to identify common attacks on the IoV system, detect the geolocation of each attacker, and specify the usage of each honeypot node from the attacker’s perspective.
{"title":"A Novel High-Interaction Honeypot Network for Internet of Vehicles","authors":"Mike Anastasiadis, K. Moschou, Kristina Livitckaia, K. Votis, D. Tzovaras","doi":"10.1109/MED59994.2023.10185669","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185669","url":null,"abstract":"Along with the evolution of communication technologies, cybersecurity has evolved, and so have its new directions and demands. There is a wide range of tools to detect, analyse, or protect systems from malicious activity. Yet, as new technologies are emerging and maturing, the need for particular domain solutions arises. This paper proposes a methodology for a honeypot network organisation mimicking vital autonomous vehicle sensors inside the Internet of Vehicles (IoV) infrastructure, along with attack propagation patterns analysis based on the logs collected from the honeypots. The discovery of sequential patterns is based on Markov Chain models applied in the honey-farm data. Further, these trained models are applied with graph-based algorithms to discover the interaction patterns between honeypots targeting the discovery of segments that were attacked in series. The intelligence produced from the analysis is used to rank and estimate the relative importance of the honeypots in their framework. The results of our study allowed us to identify common attacks on the IoV system, detect the geolocation of each attacker, and specify the usage of each honeypot node from the attacker’s perspective.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"33 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":"123304919","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/MED59994.2023.10185777
Tung K. Nguyen, S. Vlasov, D. Dobriborsci, A. Pyrkin
An adaptive algorithm, compensating for unknown harmonic disturbance acting for linear objects under conditions of the unavailable state vector with a defined delay in the control channel is proposed. One of the features of the proposed method in comparison with other methods is that the perturbation signal is considered in the form of products of sinusoids. A new approach is proposed for estimating the frequencies of harmonic signal. It is assumed that all parameters of the multiharmonic disturbance (amplitude, frequency, and phase) are unknown. The task is completed in several steps. First, an observer is constructed based on a frequency estimation scheme. Secondly, stabilization of the ouput of object to zero is carried out using feedback based on the predictor. Examples are given that confirm the relevance of the proposed approach. Our main contribution is to propose a new scheme for compensating external disturbances for a linear plant and a new approach for estimating the frequencies of a multisinusoidal signal.
{"title":"Adaptive Compensation Disturbance For Linear Systems With Input Delay*","authors":"Tung K. Nguyen, S. Vlasov, D. Dobriborsci, A. Pyrkin","doi":"10.1109/MED59994.2023.10185777","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185777","url":null,"abstract":"An adaptive algorithm, compensating for unknown harmonic disturbance acting for linear objects under conditions of the unavailable state vector with a defined delay in the control channel is proposed. One of the features of the proposed method in comparison with other methods is that the perturbation signal is considered in the form of products of sinusoids. A new approach is proposed for estimating the frequencies of harmonic signal. It is assumed that all parameters of the multiharmonic disturbance (amplitude, frequency, and phase) are unknown. The task is completed in several steps. First, an observer is constructed based on a frequency estimation scheme. Secondly, stabilization of the ouput of object to zero is carried out using feedback based on the predictor. Examples are given that confirm the relevance of the proposed approach. Our main contribution is to propose a new scheme for compensating external disturbances for a linear plant and a new approach for estimating the frequencies of a multisinusoidal signal.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"1 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":"129578346","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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