Data processing: artificial intelligence – Neural network – Structure
Reexamination Certificate
2006-07-18
2006-07-18
Hirl, Joseph P. (Department: 2129)
Data processing: artificial intelligence
Neural network
Structure
C706S015000, C706S021000
Reexamination Certificate
active
07080055
ABSTRACT:
Methods and apparatuses for backlash compensation. A dynamics inversion compensation scheme is designed for control of nonlinear discrete-time systems with input backlash. The techniques of this disclosure extend the dynamic inversion technique to discrete-time systems by using a filtered prediction, and shows how to use a neural network (NN) for inverting the backlash nonlinearity in the feedforward path. The techniques provide a general procedure for using NN to determine the dynamics preinverse of an invertible discrete time dynamical system. A discrete-time tuning algorithm is given for the NN weights so that the backlash compensation scheme guarantees bounded tracking and backlash errors, and also bounded parameter estimates. A rigorous proof of stability and performance is given and a simulation example verifies performance. Unlike standard discrete-time adaptive control techniques, no certainty equivalence (CE) or linear-in-the-parameters (LIP) assumptions are needed.
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Campos Javier
Lewis Frank L.
Board of Regents , The University of Texas System
Fulbright & Jaworski LLP
Hirl Joseph P.
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