This paper reports further development of the so-called ID Lyapunov equation based approach to the stability analysis of differential linear repetitive processes. In particular, it is shown that this approach leads to...
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A signal separation method for extracting background electroencephalogram (EEG) from EEG containing spikes was proposed. Morphological filters were designed for extracting spike waveforms, and then the background EEG ...
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A signal separation method for extracting background electroencephalogram (EEG) from EEG containing spikes was proposed. Morphological filters were designed for extracting spike waveforms, and then the background EEG was obtained by subtracting the detected spike waveforms from the EEG with spike . The proposed method was evaluated by using simulated EEG data, which consisted of a summation of EEG without spike and model waveform of typical spike. The background EEG separated by the method was processed by the automatic background EEG interpretation.
A new approach to analysis of robot stability is presented by defining the statically stable area for the foot placement. The proposed approach is applied not only to generate the free gait for a quadruped robot walki...
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A new approach to analysis of robot stability is presented by defining the statically stable area for the foot placement. The proposed approach is applied not only to generate the free gait for a quadruped robot walking in difficult terrain, but also to judge the robot stability. The effectiveness of this method is demonstrated by a practical example.
In this paper the robust fault detection and isolation (FDI) problem in linear systems, which are subjected to multiple faults and time varying system perturbations is discussed. The detection and isolation problem is...
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In this paper the robust fault detection and isolation (FDI) problem in linear systems, which are subjected to multiple faults and time varying system perturbations is discussed. The detection and isolation problem is treated by using algebraic methods and geometric design concepts. The idea of the classical Luenberger observer is generalized in an attempt that residual generators for solving the robust FDI problem can be designed.
In this paper, power system stability is addressed which includes the regular, generator-angle, transient stability and load-driven voltage instability. Flexible ac transmission systems (FACTS) devices are utilized fo...
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ISBN:
(纸本)0780352513
In this paper, power system stability is addressed which includes the regular, generator-angle, transient stability and load-driven voltage instability. Flexible ac transmission systems (FACTS) devices are utilized for improvement of power transfer capability as well as enhancement of power system stability. Techniques are developed for synthesis of nonlinear neural controllers to deal with the situation where generator dynamics and load dynamics are interlinked so that voltage instability or even voltage collapse is more likely to occur. The simulations illustrate the performance of the synthesized neural controllers. The techniques developed can be readily generalized to more general nonlinear power systems.
This paper addresses the benefits of integrating fault masking (FM) and fault detection and identification (FDI) methods to an embedded control system. It is shown that using a “smart” sensor in a Triple Modular Red...
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This paper addresses the benefits of integrating fault masking (FM) and fault detection and identification (FDI) methods to an embedded control system. It is shown that using a “smart” sensor in a Triple Modular Redundancy (TMR) configuration improves the system performance. Within the proposed hybrid system, “smart” sensors are used as redundant modules of the TMR configuration. A novel quality measure, which indicates the confidence level of a “smart” sensor output is used by a purpose-built voting algorithm to produce outputs. The proposed voting algorithm is a modification of weighted average voter, which produces results based on both the sensor output and the associated quality measure. This algorithm performs better than the conventional weighted average voter within a simple TMR configuration for low error ratios (<16). The main reason for this improvement is the capability of hybrid system to mask similar faults. Therefore, the proposed hybrid system produces more reliable results than the fault masking approach.
Describes an efficient technique for computing a hierarchical representation of the objects contained in a complex 3D scene. First, an adjacency graph keeping the costs of grouping the different pairs of objects in th...
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Describes an efficient technique for computing a hierarchical representation of the objects contained in a complex 3D scene. First, an adjacency graph keeping the costs of grouping the different pairs of objects in the scene is built. Then the minimum spanning tree (MST) of that graph is determined. A binary clustering tree (BCT) is obtained from the MST. Finally, a merging stage joins the adjacent nodes in the BCT which have similar costs. The final result is an n-ary tree which defines an intuitive clustering of the objects of the scene at different levels of abstraction. Experimental results with synthetic 3D scenes are presented.
This paper deals with the problem of H/sub /spl infin// control for a class of nonlinear systems. The system under consideration is assumed to be globally asymptotically stable with a known Lyapunov function. Based on...
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This paper deals with the problem of H/sub /spl infin// control for a class of nonlinear systems. The system under consideration is assumed to be globally asymptotically stable with a known Lyapunov function. Based on this Lyapunov function and using the notion of dissipativeness, a state feedback controller is designed which renders the closed-loop system globally asymptotically stable with a prescribed bound on the L/sub 2/-gain from the disturbance input to the controlled output. The proposed controller design method is based on the explicit construction of a Lyapunov function for the closed-loop system, which represents a significant advantage over existing methods.
Metalorganic chemical vapor deposition (MOCVD) is a promising technology for the growth of epitaxial semiconductors. It has traditionally lacked real-time growth monitoring and control, which limits the precise reprod...
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Metalorganic chemical vapor deposition (MOCVD) is a promising technology for the growth of epitaxial semiconductors. It has traditionally lacked real-time growth monitoring and control, which limits the precise reproducibility needed for high performance devices. Two complementary control approaches are investigated experimentally. The first is a feedforward disturbance rejection strategy using ultrasonic concentration measurements to reject source gas bubbler disturbances. The second is a feedback system using an ultraviolet absorption sensor for real-time monitoring of reaction chamber gas concentrations. Postgrowth X-ray analysis of InP/GaInAs superlattice test devices is used to evaluate control system performance.
Diop et al. previously (1994) proposed a general observer design methodology based upon numerical differentiation and the interpretation of observability of a system as the solvability of the system's dynamical eq...
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ISBN:
(纸本)0780352513
Diop et al. previously (1994) proposed a general observer design methodology based upon numerical differentiation and the interpretation of observability of a system as the solvability of the system's dynamical equations for the state vector in terms of a finite number of derivatives of the output and input. Numerical differentiation-base observers are alternatives to asymptotic observers for nonlinear systems. Various techniques are known to be efficient for the estimation of the few first derivatives from data with low frequency content, such as polynomial- and spline-based least squares, and averaged central differences. The main advantages of such observers are intuitiveness, flexibility and speed. However, as is the case of many inverse problems, differentiation is an ill-posed operator. This communication proposes the use of regularization to partially overcome the noise sensitivity that is inherent in the standard numerical differentiation. Regularization of numerical derivatives from experimental data consists of two operations: filtering and differentiation. Mollification is a method of filter design that is fairly well amenable to a mathematical analysis, including computation of estimation error bounds. In this method experimental data is projected onto Sobolev spaces of signals with less high frequency content, which may then be differentiated stably. The filters in question are infinite dimensional. They can be implemented approximately by means of digital Fourier transformation on finite moving windows of the data.
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