A Hybrid Neuro-Fuzzy System for Adaptive Vehicle Separation Control
Journal of VLSI Signal Processing Systems
Invariant set of weight of perceptron trained by perceptron training algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper combines a conventional method of multivariable system identification with a dynamic multi-layer perceptron (MLP) to achieve a constructive method of nonlinear system identification. The class of nonlinear systems is assumed to operate nominally around an equilibrium point in the neighborhood of which a linearized model exists to represent the system, although normal operation is not limited to the linear region. The result is an accurate discrete-time nonlinear model, extended from a MIMO linear model, which captures the nonlinear behavior of the system