By John Mingers
This is often the 1st quantity to provide entire insurance of autopoiesis-critically analyzing the idea itself and its functions in philosophy, legislation, family members treatment, and cognitive technological know-how.
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Additional resources for Self-producing systems: implications and applications of autopoiesis
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Cheng T, Lewis FL, Abu-Khalaf M (2007) Fixed-final-time-constrained optimal control of nonlinear systems using neural network HJB approach. IEEE Trans Neural Netw 18(6):1725–1736 27. Cheng T, Lewis FL, Abu-Khalaf M (2007) A neural network solution for fixed-final time optimal control of nonlinear systems. Automatica 43(3):482–490 References 21 28. Costa OLV, Tuesta EF (2003) Finite horizon quadratic optimal control and a separation principle for Markovian jump linear systems. IEEE Trans Autom Control 48:1836–1842 29.
Therefore we need to use parametric structures, such as fuzzy models [15] or neural networks, to approximate the costate function and the corresponding control law in the iterative DHP algorithm. In this subsection, we choose radial basis function (RBF) NNs to approximate the nonlinear functions. An RBFNN consists of three-layers (input, hidden and output). Each input value is assigned to a node in the input layer and passed directly to the hidden layer without weights. Nodes at the hidden layer are called RBF units, determined by a vector called center and a scalar called width.
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