The objectives of Human Engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There a...
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The objectives of Human Engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There are other benefits that are thoroughly consistent with the direction of the Navy of the future, chief among these is reduction of required numbers of personnel to operate and maintain Navy ships. The Naval Research Advisory Committee (NRAC) report on Man-Machine Technology in the Navy estimated that one of the benefits from increased application of man-machine technology to Navy ship design is personnel reduction as well as improving system availability, effectiveness, and safety The objective of this paper is to discuss aspects of the human engineering design of ships and systems that affect manning requirements, and impact human-performance and safety The paper will also discuss how the application of human engineering leads to improved performance, and crew safety, and reduced workload, all of which influence manning levels. Finally, the paper presents a discussion of tools and case studies of good human engineering design practices which reduce manning.
The evaluation of contaminant concentrations in ground water and soil is an essential aspect of most hazardous waste remedial investigations. This paper describes methods applied toward obtaining, preserving, and anal...
The evaluation of contaminant concentrations in ground water and soil is an essential aspect of most hazardous waste remedial investigations. This paper describes methods applied toward obtaining, preserving, and analyzing subsurface samples for the determination of VOC concentrations in the saturated region of an unconfined coastal plain aquifer at Dover Air Force Base (DAFB), Delaware. The described protocol involved headspace-free subsampling of cores, field preservation of subsamples in methanol, and overnight extraction of the VOCs at elevated temperature (70 degrees C). Methanol-extracted compounds were subsequently transferred to hexane and analyzed by gas chromatography. The method was found to achieve quantitative extraction from the aquifer sands in a single step, although extraction from fine-grained and more strongly sorbing aquitard samples required multiple methanol extractions to achieve comparable recovery. An extensive set of DAFB results is presented as an indication of how these methods can be applied toward characterizing field-scale contamination with a high degree of resolution and accuracy. These data have enabled a quantitative estimate of the contaminant distribution at this site and offer valuable insight into processes of contaminant migration into the underlying aquitard. In these regards, the methods used are believed to have provided much more accurate results than could have been obtained using more commonly applied techniques.
This paper proposes a hybrid quasi-ARMAX modeling and identification scheme for nonlinear systems. The idea is to incorporate a group of certain nonlinear nonparametric models (NNMs) into a linear ARMAX structure. Par...
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ISBN:
(纸本)0780335902
This paper proposes a hybrid quasi-ARMAX modeling and identification scheme for nonlinear systems. The idea is to incorporate a group of certain nonlinear nonparametric models (NNMs) into a linear ARMAX structure. Particular effort is made to find a better compromise to the trade-off between the model flexibility and the simplicity for estimation by using knowledge information efficiently. As the result, we obtain a model equipped with a linear ARMAX structure, flexibility and simplicity. The effectiveness and usefulness of the proposed hybrid model are examined by applying it to identification and control of nonlinear systems.
This paper presents a robust fault detection system (FDS) for dynamic systems with unmodeled dynamics. In the FDS, umnodeled dynamics is first qualified as soft bound, which as well as model parameters are estimated u...
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This paper presents a robust fault detection system (FDS) for dynamic systems with unmodeled dynamics. In the FDS, umnodeled dynamics is first qualified as soft bound, which as well as model parameters are estimated using a robust identification algorithm. Then as a fault detection index, Kullback discrimination information (KDI) is derived into a feasible form and an index of umnodeled dynamics is also introduced. A decision making scheme is thus developed so that fault detection is carried out based on the KDI, the index of umnodeled dynamics and other prior information about the system.
This paper describes work in progress on two extensions to the environment of a Development Framework for the design of control system software; hybrid system design and design of dependable systems. The Development F...
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This paper describes work in progress on two extensions to the environment of a Development Framework for the design of control system software; hybrid system design and design of dependable systems. The Development Framework automatically converts a control engineering specification into a parallel implementation. Hybrid controlsystems are a combination of real-time control law and discrete-state logic. The Framework can be adapted so that it may handle discrete events such as mode switching. A statechart tool, Statemate [i-Logix95], is used to specify and model discrete-state components. The design phase of the Development Framework supports the integration of the two sets of specification. Initial work to support the design of dependable systems has included the implementation of an interface between the Framework design model and the dependability modelling tool, SURF-2. Stochastic Petri net models of selected fault-tolerant mechanisms are currently supported. The models enable sensitivity analysis and comparison of competing architectures.
This paper deals with a digital adaptive control method for a manipulator mounted on a space robot after it captures an unknown object. Most control methods are based on the supposition that all physical parameters of...
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This paper deals with a digital adaptive control method for a manipulator mounted on a space robot after it captures an unknown object. Most control methods are based on the supposition that all physical parameters of the space robot are known. However, if the end-effector catches an unknown object, the physical parameters of the robot are changed, and the control performance deteriorates. In this paper, the authors propose two types of digital adaptive control algorithm using a discretized kinematic equation. computer simulation was used to make it clear that the control performance can be improved by using either of the proposed methods.
This paper presents an investigation into tne nature ot control algorithms in relation to that of the architectures for real-time applications so that a close match be forged between them. Several algorithms of regula...
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This paper presents an investigation into tne nature ot control algorithms in relation to that of the architectures for real-time applications so that a close match be forged between them. Several algorithms of regular and irregular nature are implemented on a number of architectures possessing different features. Partitioning and mapping of the algorithms, algorithm regularity and hardware and algorithm granularity are addressed in implementing the algorithms on parallel architectures. A comparison of the results of implementations is made to establish merits of the development of parallel architectures for real-time applications. Finally, the potential of heterogeneous architectures in real-time applications has been justified by the development of a three-node architecture and its performance verification in comparison to uni-processor and two-node homogeneous and heterogeneous architectures.
This paper presents significant new results on the stability and convergence properties of a general class of iterative learning control schemes derived using two-dimensional(2D) systems theory. These results apply fo...
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This paper presents significant new results on the stability and convergence properties of a general class of iterative learning control schemes derived using two-dimensional(2D) systems theory. These results apply for a general learning law which (explicitly) uses information from previous iterations or trials. A key feature of these results is that they are expressed in terms of standard linear systems theoretic properties, such as relative degree and the location of the zeros.
Repetitive, or multipass, processes are uniquely characterized by a series of sweeps, or passes through a set of dynamics defined over the so-called pass length which is finite and constant. The unique systems theoret...
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Repetitive, or multipass, processes are uniquely characterized by a series of sweeps, or passes through a set of dynamics defined over the so-called pass length which is finite and constant. The unique systems theoretic/control problem is that the sequence of outputs, or pass profiles, can contain oscillations which increase in amplitutde in the pass to pass direction. These processes can be modelled as a class of quarter plane causal 2D linear systems and this paper shows that the boundary (or pass initial) conditions alone can destabilize them. Hence they must be 'adequately modelled' in a given application and it is the boundary conditions which essentially distinguish the dynamic behaviour of linear repetitive processes from other classes of 2D linear systems.
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