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A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

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Active control of vibration using a neural network.

S D Snyder¹, N Tanaka

¹Dept. of Mech. Eng., Adelaide Univ., SA.

IEEE Transactions on Neural Networks

|January 1, 1995

Summary

This summary is machine-generated.

A novel neural network controller offers a potential replacement for traditional feedforward control systems in sound and vibration applications. While promising for nonlinear issues, further development is needed for consistent performance.

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Area of Science:

Acoustics and Control Engineering
Machine Learning Applications

Background:

Traditional feedforward control systems often utilize finite impulse response (FIR) filters and the filtered-x least mean square (LMS) algorithm.
These linear methods can be limited in addressing complex nonlinear sound and vibration control problems.

Purpose of the Study:

To develop and evaluate a neural network-based feedforward control system.
To investigate its potential to outperform or replace linear control strategies, particularly for nonlinear systems.
To ensure stable adaptation and causality within the neural control scheme.

Main Methods:

Derivation of a novel adaptive algorithm for stable neural controller adaptation.
Generalization of the linear filtered-x LMS algorithm to a neural network context.
Experimental validation comparing the proposed neural controller with a linear system.

Main Results:

The neural network controller performed comparably to the linear system on a linear control task.
The neural network controller demonstrated superior performance on a nonlinear control task.
The derived adaptive algorithm ensures stable and causal operation.

Conclusions:

The proposed neural network-based feedforward control system shows promise, especially for nonlinear sound and vibration control.
Further research is necessary to enhance performance predictability and consistency for practical implementation.
The neural controller is a potential, albeit not yet fully realized, alternative to current linear feedforward systems.