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Titlebook: Evolutionary Learning Algorithms for Neural Adaptive Control; Dimitris C. Dracopoulos Textbook 1997 Springer-Verlag London Limited 1997 Ad

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The Attitude Control Problem,s be referred to as satellite or spacecraft, since the need for attitude control systems arises frequently in aerospace technology, but the underlying definitions and methods will be generally applicable to rigid bodies.
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Current Neurocontrol Techniques,ex, noisy, nonlinear problems. The neural network approach is very attractive because of their ability to learn, to approximate functions, to classify patterns and because of their potential for massively parallel hardware implementation.
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Dynamic Systems and Control,n of change. It refers to the unfolding of events in a continuing evolutionary process. Examples from the daily life include home heating systems, the development of the economy, and population growth.
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William M. Adams,John F. Jardinen of change. It refers to the unfolding of events in a continuing evolutionary process. Examples from the daily life include home heating systems, the development of the economy, and population growth.
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https://doi.org/10.1007/978-3-658-11605-7d to meet the necessities of survival. From sense data to action, flight or the capture of prey, there is a gap that was bridged by the evolution of adaptive control systems based on circuits of simple neural components. A vital computational characteristic of such neural circuitry is the ability to model non-linear dynamic systems.
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