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Backlash compensation using neural network

Patent 6611823 Issued on August 26, 2003. Estimated Expiration Date: Icon_subject April 20, 2020. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Patent References

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Patent #: 6198246
Issued on: 03/06/2001
Inventor: Yutkowitz

Method and apparatus for tuning motion control system parameters
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Issued on: 07/10/2001
Inventor: Yutkowitz

Method and apparatus for tuning control system parameters Patent #: 6281650
Issued on: 08/28/2001
Inventor: Yutkowitz

Inventors

Assignee

Application

No. 09/553601 filed on 04/20/2000

US Classes:

706/14, ADAPTIVE SYSTEM700/44, Feed-forward (e.g., predictive)700/48, Neural network706/15, NEURAL NETWORK706/17, Approximation706/23Control

Examiners

Primary: Follansbee, John
Assistant: Booker, Kelvin

Attorney, Agent or Firm

International Class

G05B 13/02 (20060101)

Abstract

Methods and systems for backlash compensation. Restrictive assumptions on the backlash nonlinearity (e.g. the same slopes of the lines, etc.) are not required. The compensator scheme has dynamic inversion structure, with a neural network in the feedforward path that approximates the backlash inversion error plus filter dynamics needed for backstepping design. The neural network controller does not require preliminary off-line training. Neural network tuning is based on a modified Hebbian tuning law, which requires less computation than backpropagation. The backstepping controller uses a practical filtered derivative, unlike the usual differentiation required by earlier backstepping routines. Rigorous stability proofs are given using Lyapunov theory. Simulation results show that the proposed compensation scheme is an efficient way of improving the tracking performance of a vast array of nonlinear systems with backlash.

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