Pub Date : 2009-06-24DOI: 10.1109/MED.2009.5164613
T. Estrada, P. Antsaklis
In this paper we study performance-related aspects for plants in a networked control setting, employing an approach known as Model-Based Networked Control Systems (MB-NCS) with Intermittent Feedback. Model-Based Networked Control Systems use an explicit model of the plant in order to reduce the network traffic while attempting to prevent excessive performance degradation. Intermittent Feedback consists of the loop remaining closed for some time interval, then open for another interval. We begin by investigating the behavior of the system while tracking a reference input. We provide the full response of the system and a condition for stability. We then shift our attention to controller design for MB-NCS. We use dynamic programming techniques to design an optimal controller to optimize an LQ-like performance index.
{"title":"Performance of Model-Based Networked Control Systems with discrete-time plants","authors":"T. Estrada, P. Antsaklis","doi":"10.1109/MED.2009.5164613","DOIUrl":"https://doi.org/10.1109/MED.2009.5164613","url":null,"abstract":"In this paper we study performance-related aspects for plants in a networked control setting, employing an approach known as Model-Based Networked Control Systems (MB-NCS) with Intermittent Feedback. Model-Based Networked Control Systems use an explicit model of the plant in order to reduce the network traffic while attempting to prevent excessive performance degradation. Intermittent Feedback consists of the loop remaining closed for some time interval, then open for another interval. We begin by investigating the behavior of the system while tracking a reference input. We provide the full response of the system and a condition for stability. We then shift our attention to controller design for MB-NCS. We use dynamic programming techniques to design an optimal controller to optimize an LQ-like performance index.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"123 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116576529","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 : 2009-06-24DOI: 10.1109/MED.2009.5164656
A. Topalov, N. Shakev, Severina Nikolova, D. Seyzinski, O. Kaynak
A neuro-adaptive trajectory control approach for unmanned aerial vehicles is proposed. The aerial robot's altitude and latitude-longitude is controlled by three neuro-adaptive controllers that are used to track the desired altitude, airspeed and roll angle of the vehicle. Each intelligent control module consists of a conventional and a neural network feedback controller. The former is provided both to guarantee global asymptotic stability in compact space and as an inverse reference model of the response of the controlled system. Its output is used as an error signal by a stable on-line learning algorithm to update the parameters of the neurocontroller. In this way the latter is able to eliminate gradually the conventional controller from the control of the system. The proposed learning algorithm makes direct use of the variable structure systems theory and establishes a sliding motion in term of the neurocontroller parameters, leading the learning error toward zero. The performance of the proposed trajectory control scheme is evaluated with time based diagrams under MATLAB's standard configuration and the Aeronautical Simulation Block Set.
{"title":"Trajectory control of unmanned aerial vehicle using neural nets with a stable learning algorithm","authors":"A. Topalov, N. Shakev, Severina Nikolova, D. Seyzinski, O. Kaynak","doi":"10.1109/MED.2009.5164656","DOIUrl":"https://doi.org/10.1109/MED.2009.5164656","url":null,"abstract":"A neuro-adaptive trajectory control approach for unmanned aerial vehicles is proposed. The aerial robot's altitude and latitude-longitude is controlled by three neuro-adaptive controllers that are used to track the desired altitude, airspeed and roll angle of the vehicle. Each intelligent control module consists of a conventional and a neural network feedback controller. The former is provided both to guarantee global asymptotic stability in compact space and as an inverse reference model of the response of the controlled system. Its output is used as an error signal by a stable on-line learning algorithm to update the parameters of the neurocontroller. In this way the latter is able to eliminate gradually the conventional controller from the control of the system. The proposed learning algorithm makes direct use of the variable structure systems theory and establishes a sliding motion in term of the neurocontroller parameters, leading the learning error toward zero. The performance of the proposed trajectory control scheme is evaluated with time based diagrams under MATLAB's standard configuration and the Aeronautical Simulation Block Set.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131394845","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 : 2009-06-24DOI: 10.1109/MED.2009.5164543
P. Rosa, J. Shamma, C. Silvestre, M. Athans
The Stability Overlay (SO) is a “safety net” that can be integrated with virtually any multiple-model adaptive control (MMAC) architecture, guaranteeing the stability of the closed-loop system. However, the arbitrary interconnection of the SO with a MMAC architecture can lead to severe performance deterioration. Thus, this paper proposes a systematic integration of the SO with the Robust Multiple-Model Adaptive Control (RMMAC), which provides stability guarantees, while maintaining the high levels of performance of the standard RMMAC observed in numerous simulations when the design assumptions are not violated.
{"title":"Integration of the Stability Overlay (SO) with the Robust Multiple-Model Adaptive Control (RMMAC)","authors":"P. Rosa, J. Shamma, C. Silvestre, M. Athans","doi":"10.1109/MED.2009.5164543","DOIUrl":"https://doi.org/10.1109/MED.2009.5164543","url":null,"abstract":"The Stability Overlay (SO) is a “safety net” that can be integrated with virtually any multiple-model adaptive control (MMAC) architecture, guaranteeing the stability of the closed-loop system. However, the arbitrary interconnection of the SO with a MMAC architecture can lead to severe performance deterioration. Thus, this paper proposes a systematic integration of the SO with the Robust Multiple-Model Adaptive Control (RMMAC), which provides stability guarantees, while maintaining the high levels of performance of the standard RMMAC observed in numerous simulations when the design assumptions are not violated.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132789069","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 : 2009-06-24DOI: 10.1109/MED.2009.5164600
R. García-Hernández, E. Sánchez, M. Saad, E. Bayro-Corrochano
This paper deals with adaptive trajectory tracking for a five DOF robot manipulator, A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The applicability of the proposed scheme is illustrated via simulations.
{"title":"Discrete-time decentralized neural backstepping controller for a five DOF robot manipulator","authors":"R. García-Hernández, E. Sánchez, M. Saad, E. Bayro-Corrochano","doi":"10.1109/MED.2009.5164600","DOIUrl":"https://doi.org/10.1109/MED.2009.5164600","url":null,"abstract":"This paper deals with adaptive trajectory tracking for a five DOF robot manipulator, A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The HONN learning is performed online by an Extended Kalman Filter (EKF) algorithm. The applicability of the proposed scheme is illustrated via simulations.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133271043","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 : 2009-06-24DOI: 10.1109/MED.2009.5164752
S. Moustakidis, J. Theocharis, G. Giakas
A novel wavelet-based feature extraction approach is introduced in this paper for subject recognition utilizing ground reaction force (GRF) measurements. A wavelet-packet (WP) decomposition scheme is firstly proposed to recognize the discriminating frequency subbands and subsequently an efficient feature selection (FS) method is applied on the selected WP bands providing a compact set of powerful and complementary features. Our approach relies on a non-global fuzzy set-based criterion to assess the significance of every subband or feature. This local evaluation measure with respect to patterns is implemented by a fuzzy partition vector (FPV) constructed by invoking a fuzzy class allocation scheme that assigns membership grades to every class. The FS is driven by a fuzzy complementary criterion (FuzCoC) that acts upon the feature FPVs, handling simultaneously both the discrimination power and the redundancy between the features. To demonstrate the performance capabilities of our approach an extensive experimental setup is designed with tasks of increasing difficulty.
{"title":"Feature extraction based on a fuzzy complementary criterion for gait recognition using GRF signals","authors":"S. Moustakidis, J. Theocharis, G. Giakas","doi":"10.1109/MED.2009.5164752","DOIUrl":"https://doi.org/10.1109/MED.2009.5164752","url":null,"abstract":"A novel wavelet-based feature extraction approach is introduced in this paper for subject recognition utilizing ground reaction force (GRF) measurements. A wavelet-packet (WP) decomposition scheme is firstly proposed to recognize the discriminating frequency subbands and subsequently an efficient feature selection (FS) method is applied on the selected WP bands providing a compact set of powerful and complementary features. Our approach relies on a non-global fuzzy set-based criterion to assess the significance of every subband or feature. This local evaluation measure with respect to patterns is implemented by a fuzzy partition vector (FPV) constructed by invoking a fuzzy class allocation scheme that assigns membership grades to every class. The FS is driven by a fuzzy complementary criterion (FuzCoC) that acts upon the feature FPVs, handling simultaneously both the discrimination power and the redundancy between the features. To demonstrate the performance capabilities of our approach an extensive experimental setup is designed with tasks of increasing difficulty.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134166366","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 : 2009-06-24DOI: 10.1109/MED.2009.5164518
S. Koceski, N. Koceska, P. B. Zobel, F. Durante
In this paper an accurate physics-based simulation model of the 3D laser scanner, based on 2D range sensor (SICK LD-OEM1000) is presented. The model of the 2D sensor derives from the characteristics of the physical one and includes the uncertainty of the measurement, the dependency of the beam incidence angle and the target surface properties. Some experiments aimed to characterize the effects of the operation time, time autocorrection, different object surface properties and orrientations are also presented in this paper. 3D scanner virtual model, developed in rigid body dynamics environment, was verified experimentally and the resultss are reported.
{"title":"Characterization and modeling of a 3D scanner for mobile robot navigation","authors":"S. Koceski, N. Koceska, P. B. Zobel, F. Durante","doi":"10.1109/MED.2009.5164518","DOIUrl":"https://doi.org/10.1109/MED.2009.5164518","url":null,"abstract":"In this paper an accurate physics-based simulation model of the 3D laser scanner, based on 2D range sensor (SICK LD-OEM1000) is presented. The model of the 2D sensor derives from the characteristics of the physical one and includes the uncertainty of the measurement, the dependency of the beam incidence angle and the target surface properties. Some experiments aimed to characterize the effects of the operation time, time autocorrection, different object surface properties and orrientations are also presented in this paper. 3D scanner virtual model, developed in rigid body dynamics environment, was verified experimentally and the resultss are reported.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129079420","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 : 2009-06-24DOI: 10.1109/MED.2009.5164695
E. Minca, Florin Dragomir, O. Dragomir, I. Istudor
A new tool for non-autonomous hierarchical systems modelling is proposed in this article. This tool is used for the modelling of monitoring functions and integrates the fuzzy logic in the temporal aspect of the events occurrence. The tool is also suited for the development of the hierarchical and distributed typologies structures and in modelling of recurrent functions. The proposed systems are structured on hierarchical levels. On each level there are events with equal probabilities of occurrence/detection. The proposed typologies ensure a recurrent behaviour to the horizontal firing of the networks, which allows the detection of the occurrence/persistence of the monitored external events. In this context, the Recurrent Synchronized Fuzzy Petri Nets (PNetSinFREC) are well adapted to detection/decision modelling of the functions by a temporal fuzzy transition approach in hierarchical systems.
{"title":"Advanced methods for modeling of monitoring functions in hierarchical systems","authors":"E. Minca, Florin Dragomir, O. Dragomir, I. Istudor","doi":"10.1109/MED.2009.5164695","DOIUrl":"https://doi.org/10.1109/MED.2009.5164695","url":null,"abstract":"A new tool for non-autonomous hierarchical systems modelling is proposed in this article. This tool is used for the modelling of monitoring functions and integrates the fuzzy logic in the temporal aspect of the events occurrence. The tool is also suited for the development of the hierarchical and distributed typologies structures and in modelling of recurrent functions. The proposed systems are structured on hierarchical levels. On each level there are events with equal probabilities of occurrence/detection. The proposed typologies ensure a recurrent behaviour to the horizontal firing of the networks, which allows the detection of the occurrence/persistence of the monitored external events. In this context, the Recurrent Synchronized Fuzzy Petri Nets (PNetSinFREC) are well adapted to detection/decision modelling of the functions by a temporal fuzzy transition approach in hierarchical systems.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131562430","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 : 2009-06-24DOI: 10.1109/MED.2009.5164659
A. Budiyono, K. Yoon, F. Daniel
Developing an autonomous rotorcraft-based unmanned aerial vehicle presents higher level and difficult challenges than most of the robots in general. A miniature rotorcraft, with four control inputs and six degrees of freedom, has an inherently multivariable behavior that exhibits coupling effects among the different axes of motion. The dynamics of this type of aerial vehicle is characterized by instability, high-order and sensitivity to disturbance. For rotorcraft to function as a stable mobile platform in changing flight conditions, therefore, its dynamics must be understood and modeled as the basis for controlling such a vehicle. The paper presents a development of linear model of a small scale helicopter using multi input multi output time domain identification system. The results from first principle approach are used as initial condition in the Prediction Error Minimization scheme to achieve convergence. It is demonstrated that the proposed technique can enhance the accuracy of dynamics model obtained from the first principle prediction. Using the technique, the establishment of global helicopter linear model can be achieved for a practical design of linear control laws.
{"title":"Integrated identification modeling of rotorcraft-based unmanned aerial vehicle","authors":"A. Budiyono, K. Yoon, F. Daniel","doi":"10.1109/MED.2009.5164659","DOIUrl":"https://doi.org/10.1109/MED.2009.5164659","url":null,"abstract":"Developing an autonomous rotorcraft-based unmanned aerial vehicle presents higher level and difficult challenges than most of the robots in general. A miniature rotorcraft, with four control inputs and six degrees of freedom, has an inherently multivariable behavior that exhibits coupling effects among the different axes of motion. The dynamics of this type of aerial vehicle is characterized by instability, high-order and sensitivity to disturbance. For rotorcraft to function as a stable mobile platform in changing flight conditions, therefore, its dynamics must be understood and modeled as the basis for controlling such a vehicle. The paper presents a development of linear model of a small scale helicopter using multi input multi output time domain identification system. The results from first principle approach are used as initial condition in the Prediction Error Minimization scheme to achieve convergence. It is demonstrated that the proposed technique can enhance the accuracy of dynamics model obtained from the first principle prediction. Using the technique, the establishment of global helicopter linear model can be achieved for a practical design of linear control laws.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133496464","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 : 2009-06-24DOI: 10.1109/MED.2009.5164589
P. Bauer, B. Kulcsár, J. Bokor
The paper characterizes the properties of discrete time minimax tracking control problem in the case of time varying references and disturbances.
研究了具有时变参考点和扰动的离散时间极大极小跟踪控制问题的性质。
{"title":"Discrete time minimax tracking control with state and disturbance estimation II: Time-varying reference and disturbance signals","authors":"P. Bauer, B. Kulcsár, J. Bokor","doi":"10.1109/MED.2009.5164589","DOIUrl":"https://doi.org/10.1109/MED.2009.5164589","url":null,"abstract":"The paper characterizes the properties of discrete time minimax tracking control problem in the case of time varying references and disturbances.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132855773","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 : 2009-06-24DOI: 10.1109/MED.2009.5164568
G. Fourlas
Many diagnosis approaches are based in the assumption of single faults. This assumption may result to erroneous diagnosis statement in case where multiple faults occurs. Thereby multiple fault diagnosis is a challenging task especially in the control of large scale complex systems that can be viewed as hybrid systems. This owed to the fact that multiple faults are hard to detect because there consequences can mask or compensate to each other. The goal is to detect multiple faults as early as possible and provide a timely warning. A key issue is to prevent local faults to be developed into system failures that may cause safety hazards, stop temporarily the production and possible detrimental environment impact. In this work we introduce the notion of multiple faults diagnosability of Hybrid Systems in the framework of Hybrid Input Output Automata (HIOA). We present a methodology for detection of multiple faults imposing the condition for a Hybrid System to be diagnosable. This approach is applicable to a wide rage of systems since Hybrid Systems involve both continuous and discrete dynamics. The proposed method is tested via a simple application to a two tank system.
{"title":"Multiple faults diagnosability of Hybrid Systems","authors":"G. Fourlas","doi":"10.1109/MED.2009.5164568","DOIUrl":"https://doi.org/10.1109/MED.2009.5164568","url":null,"abstract":"Many diagnosis approaches are based in the assumption of single faults. This assumption may result to erroneous diagnosis statement in case where multiple faults occurs. Thereby multiple fault diagnosis is a challenging task especially in the control of large scale complex systems that can be viewed as hybrid systems. This owed to the fact that multiple faults are hard to detect because there consequences can mask or compensate to each other. The goal is to detect multiple faults as early as possible and provide a timely warning. A key issue is to prevent local faults to be developed into system failures that may cause safety hazards, stop temporarily the production and possible detrimental environment impact. In this work we introduce the notion of multiple faults diagnosability of Hybrid Systems in the framework of Hybrid Input Output Automata (HIOA). We present a methodology for detection of multiple faults imposing the condition for a Hybrid System to be diagnosable. This approach is applicable to a wide rage of systems since Hybrid Systems involve both continuous and discrete dynamics. The proposed method is tested via a simple application to a two tank system.","PeriodicalId":422386,"journal":{"name":"2009 17th Mediterranean Conference on Control and Automation","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116749460","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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