Pub Date : 2023-06-26DOI: 10.1109/MED59994.2023.10185907
W. Wang, Georg Friedrich Schuppe, Jana Tumova
We propose a decentralized solution for high-level multi-agent task planning problems in environments considering communication network failure. In particular, we consider that robots can only sense each other and communicate within a limited radius, yet, they may need to collaborate to accomplish their tasks. These tasks are given in Metric Interval Temporal Logic (MITL), which is capable to capture complex task specifications involving explicit time constraints. To substitute for the lacking communication networks, we deploy an agile robot (e.g., drones) to transfer information between the heavy-duty robots while executing tasks. We propose an algorithm to decompose each MITL formula that is assigned to the corresponding heavy-duty robot into an independent task of that robot and an independent request for others. The agile robot systematically pursues heavy-duty robots to exchange requests. The heavy-duty robots use formal methods-based algorithms to compute path plans satisfying the independent promises and the received requests. While the robots’ plan computation is fully decentralized, the satisfaction of all tasks is guaranteed (if such plans are found). The proposed solution can be applied to practical applications where the communication network fails or is restricted, such as post-catastrophe search and rescue and wildlife surveillance.
{"title":"Decentralized Multi-agent Coordination under MITL Specifications and Communication Constraints","authors":"W. Wang, Georg Friedrich Schuppe, Jana Tumova","doi":"10.1109/MED59994.2023.10185907","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185907","url":null,"abstract":"We propose a decentralized solution for high-level multi-agent task planning problems in environments considering communication network failure. In particular, we consider that robots can only sense each other and communicate within a limited radius, yet, they may need to collaborate to accomplish their tasks. These tasks are given in Metric Interval Temporal Logic (MITL), which is capable to capture complex task specifications involving explicit time constraints. To substitute for the lacking communication networks, we deploy an agile robot (e.g., drones) to transfer information between the heavy-duty robots while executing tasks. We propose an algorithm to decompose each MITL formula that is assigned to the corresponding heavy-duty robot into an independent task of that robot and an independent request for others. The agile robot systematically pursues heavy-duty robots to exchange requests. The heavy-duty robots use formal methods-based algorithms to compute path plans satisfying the independent promises and the received requests. While the robots’ plan computation is fully decentralized, the satisfaction of all tasks is guaranteed (if such plans are found). The proposed solution can be applied to practical applications where the communication network fails or is restricted, such as post-catastrophe search and rescue and wildlife surveillance.","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":"114021511","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/MED59994.2023.10185726
M. Pazera, M. Witczak, V. Puig, C. Aubrun
This paper proposes an output-feedback fault-tolerant control approach for multiple faults. The proposed approach is able to deal with both sensors and actuator faults. Moreover, the disturbances are assumed to be bounded within an ellipsoidal sets. The proposed strategy boils down to solving a set of LMIs along with an auxiliary parameter, which determines the convergence rate of the approach. Finally, the proposed strategy is illustrated with two-rotor aerodynamical system.
{"title":"An output-feedback fault-tolerant control approach for multiple faults","authors":"M. Pazera, M. Witczak, V. Puig, C. Aubrun","doi":"10.1109/MED59994.2023.10185726","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185726","url":null,"abstract":"This paper proposes an output-feedback fault-tolerant control approach for multiple faults. The proposed approach is able to deal with both sensors and actuator faults. Moreover, the disturbances are assumed to be bounded within an ellipsoidal sets. The proposed strategy boils down to solving a set of LMIs along with an auxiliary parameter, which determines the convergence rate of the approach. Finally, the proposed strategy is illustrated with two-rotor aerodynamical system.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"25 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":"114884864","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/MED59994.2023.10185876
Hyung-Jin Yoon, Chuyuan Tao, Hunmin Kim, N. Hovakimyan, P. Voulgaris
We propose a reinforcement learning framework where an agent uses an internal nominal model for stochastic model predictive control (MPC) while compensating for a disturbance. Our work builds on the existing risk-aware optimal control with stochastic differential equations (SDEs) that aims to deal with such disturbance. However, the risk sensitivity and the noise strength of the nominal SDE in the riskaware optimal control are often heuristically chosen. In the proposed framework, the risk-taking policy determines the behavior of the MPC to be risk-seeking (exploration) or risk-averse (exploitation). Specifically, we employ the risk-aware path integral control that can be implemented as a Monte-Carlo (MC) sampling with fast parallel simulations using a GPU. The MC sampling implementations of the MPC have been successful in robotic applications due to their real-time computation capability. The proposed framework that adapts the noise model and the risk sensitivity outperforms the standard model predictive path integral in simulation environments that have disturbances.
{"title":"Adaptive Risk Sensitive Path Integral for Model Predictive Control via Reinforcement Learning","authors":"Hyung-Jin Yoon, Chuyuan Tao, Hunmin Kim, N. Hovakimyan, P. Voulgaris","doi":"10.1109/MED59994.2023.10185876","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185876","url":null,"abstract":"We propose a reinforcement learning framework where an agent uses an internal nominal model for stochastic model predictive control (MPC) while compensating for a disturbance. Our work builds on the existing risk-aware optimal control with stochastic differential equations (SDEs) that aims to deal with such disturbance. However, the risk sensitivity and the noise strength of the nominal SDE in the riskaware optimal control are often heuristically chosen. In the proposed framework, the risk-taking policy determines the behavior of the MPC to be risk-seeking (exploration) or risk-averse (exploitation). Specifically, we employ the risk-aware path integral control that can be implemented as a Monte-Carlo (MC) sampling with fast parallel simulations using a GPU. The MC sampling implementations of the MPC have been successful in robotic applications due to their real-time computation capability. The proposed framework that adapts the noise model and the risk sensitivity outperforms the standard model predictive path integral in simulation environments that have disturbances.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"44 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":"134080239","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/MED59994.2023.10185857
R. Achdad, A. Rabhi, O. Pagès, J. Bosche
To improve the energy economy of a four independent wheel motor drive electric vehicle (4-IWMDEV), this paper proposes an optimal based energy-saving torque distribution. The suggested algorithm can adapt to different driving conditions while ensuring stability of the vehicle. The controller encompasses a hierarchical structure, a reference model which generates the suitable vehicle dynamics parameters, and an upper-level control that determines the integrated yaw moment and traction force. The lower-level control employs a multi-objective optimization that considers energy efficiency and steering stability to calculate the optimal torque distribution for each motor. The yaw moment control of 4-IWMDEV, integrated in the latest version of Carsim, with the classical tire workload control, were chosen to compare and evaluate the proposed controller. The simulation results show an improvement in vehicle steering stability and energy efficiency.
{"title":"Two-level Steering Stability Control Based on Energy-Saving of a Four In-Wheel Motor Drive Electric Vehicle","authors":"R. Achdad, A. Rabhi, O. Pagès, J. Bosche","doi":"10.1109/MED59994.2023.10185857","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185857","url":null,"abstract":"To improve the energy economy of a four independent wheel motor drive electric vehicle (4-IWMDEV), this paper proposes an optimal based energy-saving torque distribution. The suggested algorithm can adapt to different driving conditions while ensuring stability of the vehicle. The controller encompasses a hierarchical structure, a reference model which generates the suitable vehicle dynamics parameters, and an upper-level control that determines the integrated yaw moment and traction force. The lower-level control employs a multi-objective optimization that considers energy efficiency and steering stability to calculate the optimal torque distribution for each motor. The yaw moment control of 4-IWMDEV, integrated in the latest version of Carsim, with the classical tire workload control, were chosen to compare and evaluate the proposed controller. The simulation results show an improvement in vehicle steering stability and energy efficiency.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"73 5 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":"125997626","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/MED59994.2023.10185707
D. Henry
This paper deals with fault tolerant control for space missions. A new integral–based control allocation algorithm is developed, for optimal spacecraft actuator selection. The algorithm is developed in a general manner so that the allocation can be done under $l_{1},l_{2},l_{infty}$ optimisation criteria. Stability and convergence properties of the algorithm are formally proven, using the small gain theory and the scaled bounded real lemma. The proposed solution is evaluated through intensive simulations from a functional engineering simulator that accurately simulates an on-orbit autonomous rendezvous, on a circular orbit. The obtained results demonstrate the efficiency of the proposed fault-tolerant control allocation algorithm.
{"title":"An Integral-based Control Allocation Algorithm for Optimal Spacecraft Actuator Selection under l1, l2, l∞ Criteria for Fault Tolerance","authors":"D. Henry","doi":"10.1109/MED59994.2023.10185707","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185707","url":null,"abstract":"This paper deals with fault tolerant control for space missions. A new integral–based control allocation algorithm is developed, for optimal spacecraft actuator selection. The algorithm is developed in a general manner so that the allocation can be done under $l_{1},l_{2},l_{infty}$ optimisation criteria. Stability and convergence properties of the algorithm are formally proven, using the small gain theory and the scaled bounded real lemma. The proposed solution is evaluated through intensive simulations from a functional engineering simulator that accurately simulates an on-orbit autonomous rendezvous, on a circular orbit. The obtained results demonstrate the efficiency of the proposed fault-tolerant control allocation algorithm.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"31 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":"123936331","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/MED59994.2023.10185861
E. Manzoni, M. Rampazzo, L. Micco, F. Susin
With the help of in-vitro simulators, it is possible to simulate human physiological conditions to test medical equipment, accelerating innovation cycles and exploring the search for new and efficient solutions. In this paper, we consider the Pulse Duplicator in use at the University of Padova Healing Research Laboratory in Italy, for testing the effectiveness of prosthetic heart valves under realistic cardiac settings. By using a dither-free extremum seeking controller, that uses 1st order least squares fits for gradient estimation, we automatically adjust a fundamental system parameter in real-time, i.e. a system valve closing degree, that ensures a physiological pressure drop to simulate the peripheral resistance to flow in the human systemic circulation.
{"title":"Automatic Setup of a Pulse Duplicator Apparatus through a Dither-free ESC Approach","authors":"E. Manzoni, M. Rampazzo, L. Micco, F. Susin","doi":"10.1109/MED59994.2023.10185861","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185861","url":null,"abstract":"With the help of in-vitro simulators, it is possible to simulate human physiological conditions to test medical equipment, accelerating innovation cycles and exploring the search for new and efficient solutions. In this paper, we consider the Pulse Duplicator in use at the University of Padova Healing Research Laboratory in Italy, for testing the effectiveness of prosthetic heart valves under realistic cardiac settings. By using a dither-free extremum seeking controller, that uses 1st order least squares fits for gradient estimation, we automatically adjust a fundamental system parameter in real-time, i.e. a system valve closing degree, that ensures a physiological pressure drop to simulate the peripheral resistance to flow in the human systemic circulation.","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":"130278695","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/MED59994.2023.10185683
Danilo Menegatti, Filippo Betello, F. D. Priscoli, A. Giuseppi
Deep image inpainting is a computer vision task that uses Deep Neural Networks to generate plausible content to complete an image, for example for the restoration of a damaged image or the removal of unwanted elements captured in the picture. This paper uses deep image inpainting to restore endoscopic images that are affected by various types of artifacts. To this end, we developed a transfer learning-based procedure that uses the CSA inpainting model, which was originally proposed for unrelated tasks including the restoration of images from the Paris StreetView Dataset. The proposed system is trained and validated on the EndoCV2020 dataset, consisting of images from real endoscopies, highlighting how deep image inpainting may be a promising technology for frame restoration during medical procedures.
{"title":"Deep Image Inpainting to Support Endoscopic Procedures","authors":"Danilo Menegatti, Filippo Betello, F. D. Priscoli, A. Giuseppi","doi":"10.1109/MED59994.2023.10185683","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185683","url":null,"abstract":"Deep image inpainting is a computer vision task that uses Deep Neural Networks to generate plausible content to complete an image, for example for the restoration of a damaged image or the removal of unwanted elements captured in the picture. This paper uses deep image inpainting to restore endoscopic images that are affected by various types of artifacts. To this end, we developed a transfer learning-based procedure that uses the CSA inpainting model, which was originally proposed for unrelated tasks including the restoration of images from the Paris StreetView Dataset. The proposed system is trained and validated on the EndoCV2020 dataset, consisting of images from real endoscopies, highlighting how deep image inpainting may be a promising technology for frame restoration during medical procedures.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"85 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":"128875682","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/MED59994.2023.10185886
L. Ventura, S. Malan
Tightened diesel pollutants emissions regulations rendered the performance of steady-state map controls, which are commonly used in Internal Combustion Engine (ICE) management, unsatisfactory. To overcome these performance constraints, control systems must deal with engine transient operation, subsystem coupling and the trade-off between different requirements to efficiently manage the engine. The research demonstrates the utility of a reference generator for coordinating the air path and combustion control systems of a turbocharged diesel engine for heavy-duty applications. The control system coordinator is based on neural networks and allows following different engine-out Nitrogen Oxides (NOx) targets while satisfying the load request. The main idea is to generate air path targets, intake O2 concentration and Intake MAnifold Pressure (IMAP), in accordance with the ones of the combustion control system, engine load, in the form of Brake Mean Effective Pressure (BMEP), and NOx. As a result, the air path control system provides the global conditions for the engine proper operation, while the combustion control responds to rapid changes in the engine operating state and compensates for any remaining deviations from load and NOx targets. The reference generator, as well as the two controllers, are suitable for real-time implementation on rapid-prototyping hardware. The performance was overall good, achieving average deviations of 0.1 bar for the BMEP and 150 ppm for the NOx.
严格的柴油污染物排放法规使得内燃机(ICE)管理中常用的稳态地图控制性能不理想。为了克服这些性能限制，控制系统必须处理发动机瞬态运行、子系统耦合以及不同需求之间的权衡，以有效地管理发动机。该研究证明了参考发生器在协调重型涡轮增压柴油机的空气路径和燃烧控制系统方面的实用性。控制系统协调器基于神经网络，可以在满足负载要求的同时跟踪不同的发动机出油氮氧化物(NOx)目标。其主要思想是根据燃烧控制系统、发动机负荷的指标，以制动平均有效压力(BMEP)和NOx的形式生成气路指标、进气O2浓度和进气歧管压力(IMAP)。因此，空气路径控制系统为发动机的正常运行提供全局条件，而燃烧控制系统则对发动机运行状态的快速变化做出反应，并补偿与负荷和NOx目标的任何剩余偏差。参考发生器和两个控制器都适合在快速原型硬件上实时实现。整体性能良好，BMEP的平均偏差为0.1 bar, NOx的平均偏差为150 ppm。
{"title":"Controllers coordination for diesel engines NOx emissions management","authors":"L. Ventura, S. Malan","doi":"10.1109/MED59994.2023.10185886","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185886","url":null,"abstract":"Tightened diesel pollutants emissions regulations rendered the performance of steady-state map controls, which are commonly used in Internal Combustion Engine (ICE) management, unsatisfactory. To overcome these performance constraints, control systems must deal with engine transient operation, subsystem coupling and the trade-off between different requirements to efficiently manage the engine. The research demonstrates the utility of a reference generator for coordinating the air path and combustion control systems of a turbocharged diesel engine for heavy-duty applications. The control system coordinator is based on neural networks and allows following different engine-out Nitrogen Oxides (NOx) targets while satisfying the load request. The main idea is to generate air path targets, intake O2 concentration and Intake MAnifold Pressure (IMAP), in accordance with the ones of the combustion control system, engine load, in the form of Brake Mean Effective Pressure (BMEP), and NOx. As a result, the air path control system provides the global conditions for the engine proper operation, while the combustion control responds to rapid changes in the engine operating state and compensates for any remaining deviations from load and NOx targets. The reference generator, as well as the two controllers, are suitable for real-time implementation on rapid-prototyping hardware. The performance was overall good, achieving average deviations of 0.1 bar for the BMEP and 150 ppm for the NOx.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"20 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":"126466820","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/MED59994.2023.10185864
Dinesh Murugan, Rozhin Hajian, Milad Siami
In this paper, we investigate the performance deterioration of commensurate fractional-order consensus networks under exogenous stochastic disturbances. We formulate fractional-order differential equations for the network dynamics using Caputo derivatives and the Laplace transform, and employ the H2 norm of the dynamical system as a performance measure. By developing a graph-theoretic methodology, we relate the structural specifications of the underlying graphs to the performance measure and explicitly quantify fundamental limits on the best achievable levels of performance in fractional-order consensus networks. We also establish new connections between the sparsity of the network and the performance measure, characterizing fundamental tradeoffs that reveal the interplay between the two. Finally, we provide numerical illustrations to verify our theoretical results, which could help in the design of robust fractional-order control systems in the presence of disturbances.
{"title":"Fundamental Limits on Disturbance Propagation in Virtual Viscoelastic-based Multi-Agent Systems","authors":"Dinesh Murugan, Rozhin Hajian, Milad Siami","doi":"10.1109/MED59994.2023.10185864","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185864","url":null,"abstract":"In this paper, we investigate the performance deterioration of commensurate fractional-order consensus networks under exogenous stochastic disturbances. We formulate fractional-order differential equations for the network dynamics using Caputo derivatives and the Laplace transform, and employ the H2 norm of the dynamical system as a performance measure. By developing a graph-theoretic methodology, we relate the structural specifications of the underlying graphs to the performance measure and explicitly quantify fundamental limits on the best achievable levels of performance in fractional-order consensus networks. We also establish new connections between the sparsity of the network and the performance measure, characterizing fundamental tradeoffs that reveal the interplay between the two. Finally, we provide numerical illustrations to verify our theoretical results, which could help in the design of robust fractional-order control systems in the presence of disturbances.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"103 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":"116995071","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/MED59994.2023.10185680
E. Gershon
The problem of $H_{infty}$ state estimation is considered for uncertain polytopic linear discrete-time stochastic state-multiplicative systems. We first bring a unique version of the BRL for the latter systems which allows for vertex-dependent solution in the uncertain case. Following the BRL derivation, we solve the estimation problem for nominal systems which serves as a basis for extracting the filter parameters in the uncertain case. In both cases: the nominal and the uncertain cases, the filter parameters are extracted by a solving an LMI condition in the former case or a set of LMIs in the latter case, both of which depend on a minimal set of tuning parameters, thus greatly reduce the over-design. The theory presented is demonstrated by a numerical example.
{"title":"H∞ State estimation for stochastic state multiplicative systems","authors":"E. Gershon","doi":"10.1109/MED59994.2023.10185680","DOIUrl":"https://doi.org/10.1109/MED59994.2023.10185680","url":null,"abstract":"The problem of $H_{infty}$ state estimation is considered for uncertain polytopic linear discrete-time stochastic state-multiplicative systems. We first bring a unique version of the BRL for the latter systems which allows for vertex-dependent solution in the uncertain case. Following the BRL derivation, we solve the estimation problem for nominal systems which serves as a basis for extracting the filter parameters in the uncertain case. In both cases: the nominal and the uncertain cases, the filter parameters are extracted by a solving an LMI condition in the former case or a set of LMIs in the latter case, both of which depend on a minimal set of tuning parameters, thus greatly reduce the over-design. The theory presented is demonstrated by a numerical example.","PeriodicalId":270226,"journal":{"name":"2023 31st Mediterranean Conference on Control and Automation (MED)","volume":"198 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":"121161892","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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