The problem of constructing an "observer" to enable us to implement an approximate low sensitivity control of distributedparameter system is examined. The control is applied at the boundary of the spatial r...
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The problem of constructing an "observer" to enable us to implement an approximate low sensitivity control of distributedparameter system is examined. The control is applied at the boundary of the spatial region and the part of the control which depends on the sensitivity variables and the missing state variables is implemented via the observer.
This short paper treats the topic of suboptimal linear estimation for systems which have a finite dimensional state vector but a distributed set of observations. Such systems are of some practical interest, and are in...
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This short paper treats the topic of suboptimal linear estimation for systems which have a finite dimensional state vector but a distributed set of observations. Such systems are of some practical interest, and are indeed considerably easier to work with than most distributed parameter systems. The method proposed here is that a filter structure of linear form, driven by a statistic which is a weighted integral of the distributed observation, be used to generate estimates of the state of the system. The filter parameters, and the weighting function for the integral are selected so that the estimate is unbiased and results in minimum mean-square error, subject to the structural constraints.
The control of artificial in-stream aeration of polluted rivers with multiple waste effluent sources is treated. The optimal feedback control law for this distributedparameter system is determined by solving the part...
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In many recent applications, the control engineer is faced with the problem of controlling a linear system modeled by a transfer function of high or infinite order. In a majority of these cases it is possible and adva...
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In the above-named article [ibid., vol. AC-19, pp. 646-656, Dec. 1974], an omission in the statement of Lemma 3 is corrected. In addition, the author of a subsequent paper [D.Q. Mayne, "Canonical forms for identi...
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In the above-named article [ibid., vol. AC-19, pp. 646-656, Dec. 1974], an omission in the statement of Lemma 3 is corrected. In addition, the author of a subsequent paper [D.Q. Mayne, "Canonical forms for identification" in New Directions in Signal Proressing in Communication and Comrol, NATO Advanced Study Institute Series. Boston. MA, USA: Reldel, 1974] points out that this error has been reproduced therein as a result of the original omission.
Perturbation analysis is used to identify unknown but constant parameters in a linear distributedparameter system. Noisy observations are assumed to be available at a finite number of spatial locations. A numerical e...
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Perturbation analysis is used to identify unknown but constant parameters in a linear distributedparameter system. Noisy observations are assumed to be available at a finite number of spatial locations. A numerical example is solved to illustrate the proposed method.
Linear and nonlinear (extended Kalman-Bucy) filters are derived for systems governed by coupled partial and integro-differential equations. The framework used is sufficiently general that filters for 1) lumped paramet...
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Linear and nonlinear (extended Kalman-Bucy) filters are derived for systems governed by coupled partial and integro-differential equations. The framework used is sufficiently general that filters for 1) lumped parametersystems having multiple time varying or constant time delays, 2) coupled lumped and hyperbolic distributed parameter systems, and 3) lumped parametersystems with functional time delays, evolve as special cases. Although the filtering equations are the final result, the corresponding smoothing equations are developed as well. The performance of the filter is illustrated through application to a well stirred chemical reactor with external heat exchange.
作者：
JURY, EIUNIV CALIF
DEPT ELECT ENGN & COMP SCI BERKELEY CA 94720 USA UNIV CALIF
ELECTR RES LAB BERKELEY CA 94720 USA
It is shown how the table form of stability of linear sampleddata systems can be applied to test the stability of nonuniformly sampled and distributed parameter systems.
It is shown how the table form of stability of linear sampleddata systems can be applied to test the stability of nonuniformly sampled and distributed parameter systems.
A model for the air traffic flow between two airports subject to random constraints on the takeoff and landing capacities is set up. For a simple case a dynamic programming algorithm is used to compute the optimal sol...
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A model for the air traffic flow between two airports subject to random constraints on the takeoff and landing capacities is set up. For a simple case a dynamic programming algorithm is used to compute the optimal solutions explicitly.
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