Pub Date : 1999-09-16DOI: 10.23919/ECC.1999.7099486
John H. Steele, G. Vinnicombe
A polynomial time algorithm for converting time domain input-output data into worst case frequency domain set membership information with arbitrary precision is presented. Experimental data is assumed to be noise corrupted time domain input-output measurements for a single-input single-output linear shift invariant discrete time system. This method uses prior knowledge of bounds on both the output noise and the system impulse response. For a given finite set of frequencies, the identification algorithm calculates the set of all frequency responses which are consistent with the data and bounds. This representation of uncertainty is provably non-conservative in a certain sense for assessment of robust stabilisation of all systems which are consistent with the data and bounds. The results can be used in existing worst case frequency domain identification methods or for non-functional representations of system uncertainty.
{"title":"A non-conservative approach to set membership identification for control","authors":"John H. Steele, G. Vinnicombe","doi":"10.23919/ECC.1999.7099486","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099486","url":null,"abstract":"A polynomial time algorithm for converting time domain input-output data into worst case frequency domain set membership information with arbitrary precision is presented. Experimental data is assumed to be noise corrupted time domain input-output measurements for a single-input single-output linear shift invariant discrete time system. This method uses prior knowledge of bounds on both the output noise and the system impulse response. For a given finite set of frequencies, the identification algorithm calculates the set of all frequency responses which are consistent with the data and bounds. This representation of uncertainty is provably non-conservative in a certain sense for assessment of robust stabilisation of all systems which are consistent with the data and bounds. The results can be used in existing worst case frequency domain identification methods or for non-functional representations of system uncertainty.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116853261","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 : 1999-09-16DOI: 10.23919/ECC.1999.7100061
E. Kerrigan, J. Maciejowski
Recently, it has been shown how model predictive control (MPC) can adapt to faults in certain circumstances. This paper describes how MPC was successfully implemented as a fault-tolerant controller for a single engine/propeller model of a ship propulsion system. It is shown that the MPC controller can be tuned to be robust to internal faults that develop in the ship propulsion system, even in the absence of any fault detection and isolation (FDI) information for the internal faults. For the case of sensor faults, it is assumed that FDI information is available and it is shown how the MPC controller, in combination with a Kalman estimator, can drastically improve the tracking response of the system in the presence of sensor faults. The paper concludes that MPC is a very good candidate for a fault-tolerant controller for the ship propulsion system, requiring re-configuration only at the supervisory level, without the need for additional re-configuration in the lower-level control systems.
{"title":"Fault-tolerant control of a ship propulsion system using model predictive control","authors":"E. Kerrigan, J. Maciejowski","doi":"10.23919/ECC.1999.7100061","DOIUrl":"https://doi.org/10.23919/ECC.1999.7100061","url":null,"abstract":"Recently, it has been shown how model predictive control (MPC) can adapt to faults in certain circumstances. This paper describes how MPC was successfully implemented as a fault-tolerant controller for a single engine/propeller model of a ship propulsion system. It is shown that the MPC controller can be tuned to be robust to internal faults that develop in the ship propulsion system, even in the absence of any fault detection and isolation (FDI) information for the internal faults. For the case of sensor faults, it is assumed that FDI information is available and it is shown how the MPC controller, in combination with a Kalman estimator, can drastically improve the tracking response of the system in the presence of sensor faults. The paper concludes that MPC is a very good candidate for a fault-tolerant controller for the ship propulsion system, requiring re-configuration only at the supervisory level, without the need for additional re-configuration in the lower-level control systems.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130897196","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 : 1999-09-16DOI: 10.23919/ECC.1999.7099652
G. Vinnicombe
We define a distance between two uncertain LTI systems which provides an upper bound on the difference in worst case robust performance when the same feedback controller is used with each system. We also suggest ways of using this measure to approximate complex uncertainty descriptions with simpler ones, with a view to simplifying any subsequent robust control design step.
{"title":"Approximating uncertainty representations using the v-GAP metric","authors":"G. Vinnicombe","doi":"10.23919/ECC.1999.7099652","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099652","url":null,"abstract":"We define a distance between two uncertain LTI systems which provides an upper bound on the difference in worst case robust performance when the same feedback controller is used with each system. We also suggest ways of using this measure to approximate complex uncertainty descriptions with simpler ones, with a view to simplifying any subsequent robust control design step.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123790951","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 : 1999-09-03DOI: 10.23919/ECC.1999.7099616
Vincent Verdult, M. Verhaegen
A subspace-based algorithm for the identification of discrete-time bilinear systems is presented. The algorithm uses a subspace-based step to estimate the order of the system and to generate initial estimates of the system matrices. These matrices are iteratively refined by numerically solving a nonlinear optimization problem. The principle of separable least squares is exploited, to make the algorithm computationally efficient. The method can deal with both process and measurement noise. By means of a Monte-Carlo simulation, the method is compared with another recently proposed subspace-based algorithm for bilinear systems. It turned out that the method presented in this paper is computationally more efficient and gives more accurate models. However, sometimes the nonlinear optimization involved in the method does not converge to the global optimum and consequently the estimated model is bad.
{"title":"Subspace-based identification of MIMO bilinear systems","authors":"Vincent Verdult, M. Verhaegen","doi":"10.23919/ECC.1999.7099616","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099616","url":null,"abstract":"A subspace-based algorithm for the identification of discrete-time bilinear systems is presented. The algorithm uses a subspace-based step to estimate the order of the system and to generate initial estimates of the system matrices. These matrices are iteratively refined by numerically solving a nonlinear optimization problem. The principle of separable least squares is exploited, to make the algorithm computationally efficient. The method can deal with both process and measurement noise. By means of a Monte-Carlo simulation, the method is compared with another recently proposed subspace-based algorithm for bilinear systems. It turned out that the method presented in this paper is computationally more efficient and gives more accurate models. However, sometimes the nonlinear optimization involved in the method does not converge to the global optimum and consequently the estimated model is bad.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131269089","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 : 1999-09-03DOI: 10.23919/ECC.1999.7099320
C. T. Chou, M. Verhaegen
We consider the identification of linear state space innovations model from closed-loop data. We suggest to use the subspace closed-loop identification algorithm of [3] to obtain an initial estimate of the deterministic part of the system and then plug this estimate into the second stage of the 2CCA algorithm of Peternell et. al. [9]. The main result of this paper is to show that given closed-loop data and consistent estimates of a number of Markov parameters of the deterministic part of the system, the second stage of the 2CCA algorithm delivers consistent estimates of the system matrices of the innovations model.
{"title":"Closed-loop identification using canonical correlation analysis","authors":"C. T. Chou, M. Verhaegen","doi":"10.23919/ECC.1999.7099320","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099320","url":null,"abstract":"We consider the identification of linear state space innovations model from closed-loop data. We suggest to use the subspace closed-loop identification algorithm of [3] to obtain an initial estimate of the deterministic part of the system and then plug this estimate into the second stage of the 2CCA algorithm of Peternell et. al. [9]. The main result of this paper is to show that given closed-loop data and consistent estimates of a number of Markov parameters of the deterministic part of the system, the second stage of the 2CCA algorithm delivers consistent estimates of the system matrices of the innovations model.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126687136","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 : 1999-08-31DOI: 10.23919/ECC.1999.7099349
O. Adrot, D. Maquin, J. Ragot
This paper focuses on an original fault detection method, able to take into account parameter uncertainties described by bounded variables. Intervals offer an attractive alternative for uncertain modelling and allow a straightforward generation of adaptive thresholds. This method is based on the parity space approach. The original point treated herein concerns the choice of the parity matrix, according to uncertain matrices of state representations. After expressing external forms of parity relations, interval arithmetic is used to evaluate internal forms and to deduce residual enclosures delimiting normal operation field. Then, we stress on the problems caused by dependencies between interval variables.
{"title":"Fault detection with model parameter structured uncertainties","authors":"O. Adrot, D. Maquin, J. Ragot","doi":"10.23919/ECC.1999.7099349","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099349","url":null,"abstract":"This paper focuses on an original fault detection method, able to take into account parameter uncertainties described by bounded variables. Intervals offer an attractive alternative for uncertain modelling and allow a straightforward generation of adaptive thresholds. This method is based on the parity space approach. The original point treated herein concerns the choice of the parity matrix, according to uncertain matrices of state representations. After expressing external forms of parity relations, interval arithmetic is used to evaluate internal forms and to deduce residual enclosures delimiting normal operation field. Then, we stress on the problems caused by dependencies between interval variables.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125621823","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 : 1999-08-31DOI: 10.23919/ECC.1999.7099593
Daniel Calvelo, M. Chambrin, D. Pomorski, C. Vilhelm
We present a framework for the study of real-world time-series data using supervised Machine Learning techniques. This methodology has been developed to suit the needs of data monitoring in Intensive Care Unit, where data are highly heterogeneous. It is based on the windowed processing and monitoring of model characteristics, in order to detect changes in the model. These changes are considered to reflect the underlying systems' state transitions. We apply this framework after specializing it, based on field knowledge and ex-post corroborated assumptions.
{"title":"Decision support using machine learning: Towards intensive care unit patient state characterization","authors":"Daniel Calvelo, M. Chambrin, D. Pomorski, C. Vilhelm","doi":"10.23919/ECC.1999.7099593","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099593","url":null,"abstract":"We present a framework for the study of real-world time-series data using supervised Machine Learning techniques. This methodology has been developed to suit the needs of data monitoring in Intensive Care Unit, where data are highly heterogeneous. It is based on the windowed processing and monitoring of model characteristics, in order to detect changes in the model. These changes are considered to reflect the underlying systems' state transitions. We apply this framework after specializing it, based on field knowledge and ex-post corroborated assumptions.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114593776","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 : 1999-08-31DOI: 10.23919/ECC.1999.7099364
G. Blankenstein, A. Schaft
In this paper we investigate the notion of symmetry and reduction of implicit Hamiltonian systems. Our main result will be a theorem generalizing the classical reduction theorems for explicit Hamiltonian systems.
{"title":"Reduction of implicit hamiltonian systems with symmetry","authors":"G. Blankenstein, A. Schaft","doi":"10.23919/ECC.1999.7099364","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099364","url":null,"abstract":"In this paper we investigate the notion of symmetry and reduction of implicit Hamiltonian systems. Our main result will be a theorem generalizing the classical reduction theorems for explicit Hamiltonian systems.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123178653","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 : 1999-08-31DOI: 10.23919/ECC.1999.7100053
P. Martinet
In visual servoing applications, two main approaches were defined by Sanderson and Weiss at the beginning of the eighties: Position Based Control and Image Based Control. The aim of this article is to present different control laws using these approaches, and discuss the main advantages and disadvantages of both approaches through experimental results. The target object is composed of four non-coplanar characteristic points. From the projection of these four points in the image frame, the estimate of the Pose of the object in the sensor frame is computed using the Dementhon algorithm.
{"title":"Comparison of visual servoing techniques: Experimental results","authors":"P. Martinet","doi":"10.23919/ECC.1999.7100053","DOIUrl":"https://doi.org/10.23919/ECC.1999.7100053","url":null,"abstract":"In visual servoing applications, two main approaches were defined by Sanderson and Weiss at the beginning of the eighties: Position Based Control and Image Based Control. The aim of this article is to present different control laws using these approaches, and discuss the main advantages and disadvantages of both approaches through experimental results. The target object is composed of four non-coplanar characteristic points. From the projection of these four points in the image frame, the estimate of the Pose of the object in the sensor frame is computed using the Dementhon algorithm.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127780197","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 : 1999-08-31DOI: 10.23919/ECC.1999.7099447
A. Iggidr, A. Ouahbi, J. C. Vivaida
The aim of this paper is to show how some tools of control theory can be helpful to regulate the exploitation of a population of fish.
本文的目的是展示一些控制理论的工具如何有助于调节鱼类种群的开发。
{"title":"On the control of an exploited population of fish","authors":"A. Iggidr, A. Ouahbi, J. C. Vivaida","doi":"10.23919/ECC.1999.7099447","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099447","url":null,"abstract":"The aim of this paper is to show how some tools of control theory can be helpful to regulate the exploitation of a population of fish.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124850564","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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