Long term memory storage capacity of multiconnected neural networks
Biological Cybernetics
Nonlinear dynamical control systems
Nonlinear dynamical control systems
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Recursive neural networks for associative memory
Recursive neural networks for associative memory
Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Kolmogorov's theorem and multilayer neural networks
Neural Networks
Advanced Methods in Neural Computing
Advanced Methods in Neural Computing
Theory and applications of adaptive control-A survey
Automatica (Journal of IFAC)
Neural networks, orientations of the hypercube, and algebraic threshold functions
IEEE Transactions on Information Theory
Neurocontrol of an aircraft: Application to windshear
Mathematical and Computer Modelling: An International Journal
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Memory neuron networks for identification and control of dynamical systems
IEEE Transactions on Neural Networks
High-order neural network structures for identification of dynamical systems
IEEE Transactions on Neural Networks
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In this report, we consider the part of our work which concerns the approximation of nonlinear dynamic systems using neural networks. Based on a new paradigm of neurons with local memory (NNLM), we discuss the representation of control systems by neural networks. Using this formulation, the basic issues of controllability and observability for the dynamic system are addressed. A separation principle of learning and control is presented for NNLM, showing that the weights of the network do not affect its dynamics. Theoretical issues concerning local linearization via a coordinate transformation and nonlinear feedback are discussed. For illustration of the approach simulation results for nonlinear control of an aircraft encountering wind shear on take-off is presented.