Pub Date : 1999-08-01DOI: 10.23919/ECC.1999.7099627
M. Arahal, E. Camacho
This paper shows the application of the resource allocation network (RAN) algorithm to the problem of electrical load forecasting in a Spanish utility company. The choice of the parameters of the algorithm is usually done manually. In this paper the possibility of automatic selection of parameters is investigated. These parameters are of paramount importance since they determine the final size of the network and its capacity to generalize to new situations. The number of training samples in this kind of problems is usually small. This fact has a strong influence in methods for obtaining neural models, but is rarely taken into account in the forecasting literature. The influence of the available training data is analyzed empirically.
{"title":"Application of the RAN algorithm to the problem of short term load forecasting","authors":"M. Arahal, E. Camacho","doi":"10.23919/ECC.1999.7099627","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099627","url":null,"abstract":"This paper shows the application of the resource allocation network (RAN) algorithm to the problem of electrical load forecasting in a Spanish utility company. The choice of the parameters of the algorithm is usually done manually. In this paper the possibility of automatic selection of parameters is investigated. These parameters are of paramount importance since they determine the final size of the network and its capacity to generalize to new situations. The number of training samples in this kind of problems is usually small. This fact has a strong influence in methods for obtaining neural models, but is rarely taken into account in the forecasting literature. The influence of the available training data is analyzed empirically.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127008049","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099609
L. Steinbuch, K. Keesman
An approach is presented to design a robust PI-controller from bounded noise measurement data of a first order process with and without time delay. This controller guarantees a known robust performance. It is shown that in the case without time delay, the conservatism of the robust approach can be reduced by consciously choosing the nominal plant. The theory is illustrated to a first-order process with time delay but it can be extended to second order plants with more general PID-controllers.
{"title":"From bounded-noise data to robust PI-controller design","authors":"L. Steinbuch, K. Keesman","doi":"10.23919/ECC.1999.7099609","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099609","url":null,"abstract":"An approach is presented to design a robust PI-controller from bounded noise measurement data of a first order process with and without time delay. This controller guarantees a known robust performance. It is shown that in the case without time delay, the conservatism of the robust approach can be reduced by consciously choosing the nominal plant. The theory is illustrated to a first-order process with time delay but it can be extended to second order plants with more general PID-controllers.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130590756","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099377
W. Byrski, S. Fuksa
In the paper the new idea of the calculation of eigenvalues and eigenvectors for time dependent matrix G(t) is presented. This algorithm is based on the solution of some nonlinear differential equation which is fulfilled on eigenvectors Q(t) of matrix G(t) and it is faster than classical methods for eigenproblem solution. The solution has some properties of local stability especially for the states near the minimal eigenvector. Hence it can be used in on-line application (for each t). The application of this algorithm to solution of optimal parameter identification of continuous SISO systems is also pointed. (is presented).
{"title":"Time variable gram matrix eigenproblem and its application to optimal identification of continuous systems","authors":"W. Byrski, S. Fuksa","doi":"10.23919/ECC.1999.7099377","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099377","url":null,"abstract":"In the paper the new idea of the calculation of eigenvalues and eigenvectors for time dependent matrix G(t) is presented. This algorithm is based on the solution of some nonlinear differential equation which is fulfilled on eigenvectors Q(t) of matrix G(t) and it is faster than classical methods for eigenproblem solution. The solution has some properties of local stability especially for the states near the minimal eigenvector. Hence it can be used in on-line application (for each t). The application of this algorithm to solution of optimal parameter identification of continuous SISO systems is also pointed. (is presented).","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121204790","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099550
L. Finesso, L. Gerencsér, I. Kmecs
The purpose of this paper is to formulate and study the problem of system identification with Gaussian noise and quantized observations. The prime examples that we study are Gaussian AR(1)-systems and the simplest Gaussian linear regression. The main results of the paper are the development of a randomization technique for the effective solution of the likelihood equation and computational experiments to demonstrate the paradoxical role of noise.
{"title":"Estimation of parameters from quantized noisy observations","authors":"L. Finesso, L. Gerencsér, I. Kmecs","doi":"10.23919/ECC.1999.7099550","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099550","url":null,"abstract":"The purpose of this paper is to formulate and study the problem of system identification with Gaussian noise and quantized observations. The prime examples that we study are Gaussian AR(1)-systems and the simplest Gaussian linear regression. The main results of the paper are the development of a randomization technique for the effective solution of the likelihood equation and computational experiments to demonstrate the paradoxical role of noise.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121231460","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 : 1999-08-01DOI: 10.23919/ECC.1999.7098749
J. H. Liu, P. Frank
This paper studies the problem of H∞ detection filter design for state delayed linear continuous-time systems with parameter uncertainty, in which the effects of faults and disturbances cannot be de-coupled from each other. The detection filter gains are designed so that, if the fault of the system is absent, the filter is convergent for the admissible uncertainty conditions. The transfer function from disturbances to residual satisfies the prespecified constraint of H∞ norm upper bound. Simultaneously, the design freedom can be used to achieve the extreme value of the residual-to-faults sensitivity.
{"title":"H∞ detection filter design for state delayed linear systems with parameter uncertainty","authors":"J. H. Liu, P. Frank","doi":"10.23919/ECC.1999.7098749","DOIUrl":"https://doi.org/10.23919/ECC.1999.7098749","url":null,"abstract":"This paper studies the problem of H∞ detection filter design for state delayed linear continuous-time systems with parameter uncertainty, in which the effects of faults and disturbances cannot be de-coupled from each other. The detection filter gains are designed so that, if the fault of the system is absent, the filter is convergent for the admissible uncertainty conditions. The transfer function from disturbances to residual satisfies the prespecified constraint of H∞ norm upper bound. Simultaneously, the design freedom can be used to achieve the extreme value of the residual-to-faults sensitivity.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"373 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114087593","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099499
H. Unbehauen, J. Dastych, Heribert Werthes, M. Bennauer
This paper deals with the analysis and design of controllers for speed control loops. Taking a steam turbine as an example the design of robust control systems and the examination of uncertain plant parameters will be carried out by graphically representing the controller and the plant parameters. The analysis of the plant and the controller design is supported by a power plant simulation system.
{"title":"Simulation and robust control of power plants","authors":"H. Unbehauen, J. Dastych, Heribert Werthes, M. Bennauer","doi":"10.23919/ECC.1999.7099499","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099499","url":null,"abstract":"This paper deals with the analysis and design of controllers for speed control loops. Taking a steam turbine as an example the design of robust control systems and the examination of uncertain plant parameters will be carried out by graphically representing the controller and the plant parameters. The analysis of the plant and the controller design is supported by a power plant simulation system.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114633611","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 : 1999-08-01DOI: 10.23919/ECC.1999.7100044
Yongji Wang, Hong Wang
A nonlinear model predictive control based on pseudolinear neural network (PNN) is proposed, in which the second order based optimization is adopted. The recursive computation of Jacobian matrix is also proposed. The stability analysis of the closed loop model predictive control system is presented based on Lyapunov theory. From the stability investigation, the sufficient condition for the asymptotic stability of the neural predictive control system is obtained. The simulated example of the continuous stirred tank reactor (CSTR) illustrated the satisfactory result based on the proposed control strategy in this paper.
{"title":"A nonlinear model predictive control based on pseudolinear neural networks","authors":"Yongji Wang, Hong Wang","doi":"10.23919/ECC.1999.7100044","DOIUrl":"https://doi.org/10.23919/ECC.1999.7100044","url":null,"abstract":"A nonlinear model predictive control based on pseudolinear neural network (PNN) is proposed, in which the second order based optimization is adopted. The recursive computation of Jacobian matrix is also proposed. The stability analysis of the closed loop model predictive control system is presented based on Lyapunov theory. From the stability investigation, the sufficient condition for the asymptotic stability of the neural predictive control system is obtained. The simulated example of the continuous stirred tank reactor (CSTR) illustrated the satisfactory result based on the proposed control strategy in this paper.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116328005","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099489
J. Stoustrup, G. Aglietti, E. Rogers, R. Langley, Stephen B. Gabriel
The suppression of microvibrations (low amplitude vibrations with frequencies in the range 1 to 1000 Hz) is becoming increasingly important in spacecraft and other applications and can only be achieved (in most cases) by active feedback control schemes. This paper describes a Lagrange-Rayleigh-Ritz method which has been used to develop a state space description of the generic case of a vibrating panel with piezo-electric patches as actuators and sensors, disturbances, and a payload. The resulting models are used here to design H∞ based active feedback control schemes for disturbance attenuation.
{"title":"H∞ controllers for the rejection of microvibration disturbances","authors":"J. Stoustrup, G. Aglietti, E. Rogers, R. Langley, Stephen B. Gabriel","doi":"10.23919/ECC.1999.7099489","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099489","url":null,"abstract":"The suppression of microvibrations (low amplitude vibrations with frequencies in the range 1 to 1000 Hz) is becoming increasingly important in spacecraft and other applications and can only be achieved (in most cases) by active feedback control schemes. This paper describes a Lagrange-Rayleigh-Ritz method which has been used to develop a state space description of the generic case of a vibrating panel with piezo-electric patches as actuators and sensors, disturbances, and a payload. The resulting models are used here to design H∞ based active feedback control schemes for disturbance attenuation.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114782221","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 : 1999-08-01DOI: 10.23919/ECC.1999.7100051
J. Gangloff, M. Mathelin, G. Abba
This paper presents a new approach to high speed visual servoing in the case of a 6 DOF industrial manipulator that takes into account the dynamics of the manipulator in the synthesis of the visual controller. The manipulator with its actuators (DC motors), their current feedback loops and their velocity control loops, is modelled as a "virtual Cartesian motion device". A linearized model of the dynamics is identified around working configurations of the manipulator. Then, based on this higher order model of the dynamics of the manipulator, 6 Generalized Predictive Controllers (GPC) are implemented on line. Simulations and experimental results show a drastic improvement in performance for a 6 DOF industrial manipulator in an eye-in-hand configuration with a high speed visual servo-loop (120 Hz) compared to standard approaches neglecting these dynamics.
{"title":"High performance 6 DOF visual servoing using Generalized Predictive Control","authors":"J. Gangloff, M. Mathelin, G. Abba","doi":"10.23919/ECC.1999.7100051","DOIUrl":"https://doi.org/10.23919/ECC.1999.7100051","url":null,"abstract":"This paper presents a new approach to high speed visual servoing in the case of a 6 DOF industrial manipulator that takes into account the dynamics of the manipulator in the synthesis of the visual controller. The manipulator with its actuators (DC motors), their current feedback loops and their velocity control loops, is modelled as a \"virtual Cartesian motion device\". A linearized model of the dynamics is identified around working configurations of the manipulator. Then, based on this higher order model of the dynamics of the manipulator, 6 Generalized Predictive Controllers (GPC) are implemented on line. Simulations and experimental results show a drastic improvement in performance for a 6 DOF industrial manipulator in an eye-in-hand configuration with a high speed visual servo-loop (120 Hz) compared to standard approaches neglecting these dynamics.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124501623","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 : 1999-08-01DOI: 10.23919/ECC.1999.7099771
V. Ugrinovskii, I. Petersen
In this paper, we consider a filtering problem for stochastic uncertain systems. The uncertainty in the system is characterized in terms of an uncertain probability distribution on the noise input. This uncertainty is assumed to satisfy a certain relative entropy constraint. The solution to a specially parametrized risk-sensitive stochastic filtering problem is used to construct a filter for the uncertain system which guarantees a certain upper bound on the filtering error. This solution is obtained by solving a pair of algebraic Riccati equations. The corresponding filtering error bound holds for all admissible uncertainties.
{"title":"Robust filtering for continuous-time stochastic uncertain systems with relative entropy constraints","authors":"V. Ugrinovskii, I. Petersen","doi":"10.23919/ECC.1999.7099771","DOIUrl":"https://doi.org/10.23919/ECC.1999.7099771","url":null,"abstract":"In this paper, we consider a filtering problem for stochastic uncertain systems. The uncertainty in the system is characterized in terms of an uncertain probability distribution on the noise input. This uncertainty is assumed to satisfy a certain relative entropy constraint. The solution to a specially parametrized risk-sensitive stochastic filtering problem is used to construct a filter for the uncertain system which guarantees a certain upper bound on the filtering error. This solution is obtained by solving a pair of algebraic Riccati equations. The corresponding filtering error bound holds for all admissible uncertainties.","PeriodicalId":117668,"journal":{"name":"1999 European Control Conference (ECC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126284847","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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