Constrained supremum and supremum operators are introduced to obtain a general procedure for computing supremal elements of upper semilattices. Examples of such elements include supremal (A,B)-invariant subspaces in l...
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(纸本)0780341872
Constrained supremum and supremum operators are introduced to obtain a general procedure for computing supremal elements of upper semilattices. Examples of such elements include supremal (A,B)-invariant subspaces in linear system theory and supremal controllable sublanguages in discrete-event system theory. For some examples, we show that the algorithms available in the literature are special cases of our procedure.
In this paper we present a method for image feature extraction using coordinate logic filters. Coordinate logic filters constitute a new kind of nonlinear filter, which are closely related to morphological fillers. Th...
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In this paper we present a method for image feature extraction using coordinate logic filters. Coordinate logic filters constitute a new kind of nonlinear filter, which are closely related to morphological fillers. The key issue to the coordinate logic analysis of images is the methodology of fast successive filtering and managing of the residues. The desired processing is succeeded by executing only direct logic operations among the pixels of the given image. The coordinate logic filters can be easily implemented using logic circuits or cellular automata.
This research is concerned with fault detection of nonlinear systems using Kullback discrimination information (KDI) as an index. A hybrid quasi-ARMAX model is proposed, which combines a linear ARMAX model and a multi...
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This research is concerned with fault detection of nonlinear systems using Kullback discrimination information (KDI) as an index. A hybrid quasi-ARMAX model is proposed, which combines a linear ARMAX model and a multi-ARX-model based on interpolation. In the case where the faults occur on the ARMAX model part, a KDI-based "robust" fault detection is performed, in which multi-ARX-model part is treated as error due to nonlinear undermodeling. In other cases, the model is transformed into several local ARMAX models and fault detection is performed by using the KDI to discriminate each identified local model. In this paper, we mainly concentrate our discussion on the latter cases.
This paper deals with manipulation of a floating object by two space robots with manipulators. It is shown in this paper that a total system consisting of two robots and a floating object could be treated as a distrib...
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This paper deals with manipulation of a floating object by two space robots with manipulators. It is shown in this paper that a total system consisting of two robots and a floating object could be treated as a distributed system, and then a new generalized Jacobian matrix (GJM) is defined. Moreover, it is confirmed that this type of GJM is effective for using adaptive control for decreasing the amount of calculation for the control algorithm.
When designing conventional controllers for multivariable systems, the general approach often adopted is to find a suitable nominal model for the plant, which is often a very difficult task, and then to design a contr...
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When designing conventional controllers for multivariable systems, the general approach often adopted is to find a suitable nominal model for the plant, which is often a very difficult task, and then to design a controller based upon this model. If, however, large unexpected structural changes subsequently occur in the system, severe limitations in practical performance may occur since conventional control schemes usually do not have the ability to controlsystems which are subject to unplanned extreme changes. Moreover, for the realistic situation when a control input constraint exists, few results for continuous time multivariable systems are available. In this paper, a continuation of the author's earlier work is presented for a class of self-tuning proportional-integral-derivative controllers for open loop asymptotically stable MIMO systems. Results of this new controller when applied to several multivariable systems will also be described.
In the pursue of providing high quality output regulation and the minimization of energy costs for industrial plants, it has become important to develop high performance servomechanism controllers . Under nominal oper...
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In the pursue of providing high quality output regulation and the minimization of energy costs for industrial plants, it has become important to develop high performance servomechanism controllers . Under nominal operating conditions, such controllers are generally found to be satisfactory. However, severe limitations in performance in such systems often occur when large unanticipated structural controllers which have this property as being ‘intelligent’ . This paper gives an overview of a class of intelligent servomechanism controllers , which is based on the results of [Miller, Davison (1989)], [Change, Davison (1994a)] (Sec. 7.3). These controllers contain a switching device which applies a sequence of LTI controllers to the system, and which after a finite time (i.e. ‘learning time’), switching ceases, resulting in the system being controlled by a LTI controller; the parameters of this LTI controller are then adjusted by on-line tuning to minimize a performance index for the system.
In this paper is presented a new approach to robust non-linear control design, which can guarantee a prescribed decay rate of exponential stability for known system uncertainties. The proposed approach doesn’t employ...
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In this paper is presented a new approach to robust non-linear control design, which can guarantee a prescribed decay rate of exponential stability for known system uncertainties. The proposed approach doesn’t employ matching conditions. The non-linear power system with deterministic uncertainties is chosen as demonstration example.
Many researches for linear parameter varying systems focus on the approach using a parameter-dependent Lyapunov function. Analysis and controller design for linear parameter varying systems are characterized by parame...
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Many researches for linear parameter varying systems focus on the approach using a parameter-dependent Lyapunov function. Analysis and controller design for linear parameter varying systems are characterized by parameter-dependent linear matrix inequalities (LMIs). We propose an approach to solving parameter-dependent LMI conditions based on a finite number of LMI conditions. The proposed method does not require any particular assumptions on the parameter dependence except continuity. We consider a class of linear parameter varying systems and apply the proposed technique to analysis of their L/sup 2/ gain. Finally we demonstrate its efficacy by a numerical case study.
The paper describes the development and application of several techniques for knowledge extraction from trained ANN models, such as the identification of redundant inputs and hidden neurons, derivation of causal relat...
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The paper describes the development and application of several techniques for knowledge extraction from trained ANN models, such as the identification of redundant inputs and hidden neurons, derivation of causal relationships between inputs and outputs, and analysis of the hidden neuron behavior in classification ANNs. An example of the application of these techniques is given of the faulty LED display benchmark. References of the application of these techniques are given of diverse large scale ANN models of industrial processes.
This paper makes use of a matched-filterbank (MAFI) approach to study the forward-only and forward-backward Capon (termed FCapon and FBCapon, respectively) as well as the forward-only and forward-backward APES (FAPES ...
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This paper makes use of a matched-filterbank (MAFI) approach to study the forward-only and forward-backward Capon (termed FCapon and FBCapon, respectively) as well as the forward-only and forward-backward APES (FAPES and FBAPES, respectively) estimators for complex spectral estimation. In particular, we prove that, to within a second-order approximation: (a) FCapon and FBCapon are both biased downward; (b) the bias of FBCapon is half that of FCapon; and (c) FAPES and FBAPES are both unbiased. We also show that computationally the APES estimators are only slightly more involved than the Capon (1969) estimators. A natural and logical conclusion of this paper follows as the preference of APES over the Capon estimators in most applications. Numerical examples are also presented to demonstrate quantitatively the properties of the estimators under study.
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