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Neural-net computing and the intelligent control of systems

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TLDR
It is shown that systems identification can indeed be achieved in the presence of noise and that optimal control can be formulated in a learning mode, by neural nets.
Abstract
In this article, we are concerned with neural-nets which can learn to control systems in accordance with a guiding intent, and can also learn how to formulate that control strategy or intent. The overall task of systems control is viewed as being carried out by four components, these being the predictive monitoring net, the control action generator net, the objective function net and the optimization net. This approach and perspective are described and illustrated in this article. In our examples, we show that systems identification can indeed be achieved in the presence of noise and that optimal control can be formulated in a learning mode, by neural nets.

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Citations
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Journal ArticleDOI

Learning and generalization characteristics of the random vector functional-link net

TL;DR: The learning and generalization characteristics of the random vector version of the Functional-link net are explored and compared with those attainable with the GDR algorithm and it seems that ‘ overtraining ’ occurs for stochastic mappings.
Journal ArticleDOI

Stochastic choice of basis functions in adaptive function approximation and the functional-link net

TL;DR: A theoretical justification for the random vector version of the functional-link (RVFL) net is presented, based on a general approach to adaptive function approximation, which results are that the RVFL is a universal approximator for continuous functions on bounded finite dimensional sets.

Approved for Public Release; Distribution is Unlimited

TL;DR: LaRonde as mentioned in this paper analyzes the conflict in Xinjiang and concludes that the Chinese continue to defeat the separatist movement through a strategy that counters Mao's seven fundamentals of revolutionary warfare, concluding that Mao, as well as the communist leaders who followed him, was also successful at waging protracted counterinsurgency.
Journal ArticleDOI

Review of the applications of neural networks in chemical process control : simulation and online implementation

TL;DR: The review reveals the tremendous prospect of using neural networks in process control and shows the multilayered neural network as the most popular network for such process control applications and also shows the lack of actual successful online applications at the present time.
Journal ArticleDOI

Identification of nonlinear dynamic systems using functional link artificial neural networks

TL;DR: An alternate ANN structure called functional link ANN (FLANN) for nonlinear dynamic system identification using the popular backpropagation algorithm and performs as good as and in some cases even better than the MLP structure for the problem of nonlinear system identification.
References
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Journal ArticleDOI

Multilayer feedforward networks are universal approximators

TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Book

Nonlinear Control Systems

TL;DR: In this paper, a systematic feedback design theory for solving the problems of asymptotic tracking and disturbance rejection for linear distributed parameter systems is presented, which is intended to support the development of flight controllers for increasing the high angle of attack or high agility capabilities of existing and future generations of aircraft.
Journal ArticleDOI

Identification and control of dynamical systems using neural networks

TL;DR: It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems and the models introduced are practically feasible.
Book

Adaptive Control

TL;DR: Benefiting from the feedback of users who are familiar with the first edition, the material has been reorganized and rewritten, giving a more balanced and teachable presentation of fundamentals and applications.
Journal ArticleDOI

Fuzzy logic in control systems: fuzzy logic controller. II

TL;DR: The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined and several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated.
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