In this paper, a multi-granularity software rejuvenation policy isstudied. Four granularities of rejuvenation are proposed tomitigate the impact of four levels of software aging *** Time Markov Chain (CTMC) model is u...
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In this paper, a multi-granularity software rejuvenation policy isstudied. Four granularities of rejuvenation are proposed tomitigate the impact of four levels of software aging *** Time Markov Chain (CTMC) model is used to obtain the availability and cost from its closed form solution. Moreover, therelations between availability, cost and parameters are studied and the optimal selection of parameters is obtained accordingly. Numerical examples show that the optimal inspection rates for maximizing availability and minimizing cost become larger if inspection delay rate becomes lower, and also the optimal inspection rates have the property of phase transitions when inspection delay rate changes.
Grading is the process of subdividing a diagnostic category to increase the amount of information in a histopathology report and so assist clinicians in making individual therapeutic decisions. A good grading system w...
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In this paper, a state-feedback strategies based on time-scale separation technique for a class of strict-feedback systems in the presence of unstructured uncertainties is proposed which recovers the state trajectorie...
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In this paper, a state-feedback strategies based on time-scale separation technique for a class of strict-feedback systems in the presence of unstructured uncertainties is proposed which recovers the state trajectories of a nominal control design (without uncertainties) in the presence of unmatched uncertain nonlinearities. The performance of the feedback control scheme is evaluated by simulating state-feedback control for an uncertain strict-feedback system.
This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. The cerebellar controller is a modified MOSAIC model which adaptively controls the arm. We call this model ORF-MOSAIC (Orga...
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ISBN:
(纸本)9781457721366
This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. The cerebellar controller is a modified MOSAIC model which adaptively controls the arm. We call this model ORF-MOSAIC (Organized by Receptive Fields MOdular Selection And Identification for control). The arm features a musculoskeletal model which is controlled through muscle activations by means of optimization techniques. With as few as 16 modules, we were able to control the arm in a workspace of 30×30 cm. The system was able to adapt to an external field as well as handling new objects despite delays. The discussion section suggests that there are similarities between the microzones in the cerebellum and the modules of this new model.
Abstract In this paper, we address the data-driven design of observers for the process monitoring and control purposes. Instead of identifying a standard state space model, our design schemes are based on the identifi...
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Abstract In this paper, we address the data-driven design of observers for the process monitoring and control purposes. Instead of identifying a standard state space model, our design schemes are based on the identification of the so-called parity subspace. Two design schemes are developed, which allow a direct design of (a) observer-based fault detection systems (b) a full order observer for the estimation of the process state variables. The achieved results are illustrated by a benchmark example.
The dynamic behavior of rotor containing crack is a subject of particular interest and has been extensively investigated by researchers. The effects of crack on the natural frequencies and modal shapes and motion orbi...
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Experiment design for quantum channel parameter estimation includes the design of the quantum input to the channel and the observables to be applied on the resulting quantum output system, called the experiment config...
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Robots used in manufacturing today are tailored to their tasks by system integration based on expert knowledge concerning both production and machine control. For upcoming new generations of even more flexible robot s...
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Robots used in manufacturing today are tailored to their tasks by system integration based on expert knowledge concerning both production and machine control. For upcoming new generations of even more flexible robot solutions, in applications such as dexterous assembly, the robot setup and programming gets even more challenging. Reuse of solutions in terms of parameters, controls, process tuning, and of software modules in general then gets increasingly important. There has been valuable progress within reuse of automation solutions when machines comply with standards and behave according to nominal models. However, more flexible robots with sensor-based manipulation skills and cognitive functions for human interaction are far too complex to manage, and solutions are rarely reusable since knowledge is either implicit in imperative software or not captured in machine readable form. We propose techniques that build on existing knowledge by converting structured data into an RDF-based knowledge base. By enhancements of industrial controlsystems and available engineering tools, such knowledge can be gradually extended as part of the interaction during the definition of the robot task.
The hybrid minimum principle (HMP) is extended to hybrid systems with autonomous (internally forced) switching on switching manifolds, controlled (externally forced) switching, jumps of the continuous state when switc...
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ISBN:
(纸本)9781612848006
The hybrid minimum principle (HMP) is extended to hybrid systems with autonomous (internally forced) switching on switching manifolds, controlled (externally forced) switching, jumps of the continuous state when switching, and time-varying functions for specifying the continuous and discrete dynamics. The formulation of the hybrid optimal control problem (HOCP) includes running, switching, and terminal costs. The HMP provides necessary optimality conditions for a solution of the HOCP and can be used as basis for developing numerical optimal control algorithms.
A discrete-time sliding-mode control for the trajectory tracking problem of four driving-steering wheels (4DW/SW) autonomous vehicle SEEKUR is presented in this paper. SEEKUR is a holonomic, all-weather, outdoor robot...
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