This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learn...
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ISBN:
(纸本)9781846000386
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learning outcomes to give a coherent student experience. Finally, it uses examples to illustrate where the web and other technology can be invaluable tools for the delivery of a holistic curriculcum.
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learn...
详细信息
ISBN:
(纸本)9781627481199
This paper proposes and gives evidence supporting a team based approach to the design and implementation of engineering curricula. It shows how such an approach allows the effective integration of many different learning outcomes to give a coherent student experience. Finally, it uses examples to illustrate where the web and other technology can be invaluable tools for the delivery of a holistic curriculcum.
Rolls-Royce is developing a Full Authority Digital Electronic control (FADEC) product line for helicopter and light turboprop applications. This is driven by market demand to reduce the proportional cost of control sy...
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Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of ...
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Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of more general adaptive systems. Following an introduction to the simple GA, important characteristics of GA are identified and control applications are described.< >
Developments in computational models of evolutionary processes have led to the realization of powerful, robust, and general optimization and adaptive systems collectively called evolutionary algorithms. In this paper,...
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Developments in computational models of evolutionary processes have led to the realization of powerful, robust, and general optimization and adaptive systems collectively called evolutionary algorithms. In this paper, we consider one member of this class of algorithms, the genetic algorithm, and describe the features and characteristics that are particularly appropriate for applications in controlsystemsengineering. The versatility and robust qualities of the algorithm are considered and a number of application areas described. Some prospective future directions are also identified.
Rolls-Royce is developing a Full Authority Digital Electronic control (FADEC) product line for helicopter and light turboprop applications. This is driven by market demand to reduce the proportional cost of control sy...
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Recent research into the mechanisms of evolution and genetics has shown how biological systems have managed to develop some very powerful methods of optimising and adapting themselves to meet new environmental challen...
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Recent research into the mechanisms of evolution and genetics has shown how biological systems have managed to develop some very powerful methods of optimising and adapting themselves to meet new environmental challenges. For applications in controlsystemsengineering, many of the characteristics exhibited by genetic algorithms are particularly appropriate. They can be used as an optimization tool or as the basis of adaptive systems. The versatile and robust qualities of these algorithms are reviewed and their relevance for controlsystems is highlighted. Applications are described and implementation issues are addressed, including parallelization. Prospective future directions are identified
Cigarette smoking remains a major public health issue. Despite a variety of treatment options, existing intervention protocols intended to support attempts to quit smoking have low success rates. An emerging treatment...
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ISBN:
(纸本)9781479901777
Cigarette smoking remains a major public health issue. Despite a variety of treatment options, existing intervention protocols intended to support attempts to quit smoking have low success rates. An emerging treatment framework, referred to as adaptive interventions in behavioral health, addresses the chronic, relapsing nature of behavioral health disorders by tailoring the composition and dosage of intervention components to an individual's changing needs over time. An important component of a rapid and effective adaptive smoking intervention is an understanding of the behavior change relationships that govern smoking behavior and an understanding of intervention components' dynamic effects on these behavioral relationships. As traditional behavior models are static in nature, they cannot act as an effective basis for adaptive intervention design. In this article, behavioral data collected daily in a smoking cessation clinical trial is used in development of a dynamical systems model that describes smoking behavior change during cessation as a self-regulatory process. Drawing from controlengineering principles, empirical models of smoking behavior are constructed to reflect this behavioral mechanism and help elucidate the case for a control-oriented approach to smoking intervention design.
This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where th...
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This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown ***-policy and off-policy learning algorithms are developed to solve the stochastic zero-sum games,where the system dynamics is not *** analyzing the value function iterations,the convergence of the model-based algorithm is *** equivalence of several types of value iteration algorithms is *** effectiveness of model-free algorithms is demonstrated by a numerical example.
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