Proceedings ArticleDOI
An introspective algorithm for achieving low-gain high-performance robust neural-adaptive control
Chris J. B. Macnab
- pp 2893-2899
TLDR
In this paper, a describing function analysis establishes stability assuming an accurate measure of the partial derivative in neural-adaptive control schemes using the method of describing functions.Abstract:
A method proposed for halting weight drift in neural-adaptive control schemes is analyzed using the method of describing functions. The method utilizes a self-evaluating, introspective method with a Cerebellar Model Arithmetic Computer. The average error within the domain of local basis functions is measured, and then used to estimate the effect of weight updates on reducing the error i.e. estimating a partial derivative. The adaptation algorithm halts the weight updates when it is determined that weight updates are no longer beneficial in reducing the average error. In this paper, a describing function analysis establishes stability assuming an accurate measure of the partial derivative.read more
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A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
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Book
Stability of adaptive controllers
TL;DR: The concise, critical reviews in this article cover recent advances in the field of xenobiotics in any segment of the environment and address areas of accomplishment and need and discuss toxicological implications.
Journal ArticleDOI
Preventing bursting in approximate-adaptive control when using local basis functions
TL;DR: This work proposes a new robust adaptation method that prevents bursting in low-gain approximate-adaptive controls that utilize local basis functions and adds two additional approximators to estimate each nonlinear function.
Proceedings ArticleDOI
An Introspective Learning Algorithm that Achieves Robust Adaptive Control of a Quadrotor Helicopter.
Khalid Masaud,Chris J. B. Macnab +1 more
TL;DR: Simulation results with a quadrotor helicopter show this novel approach can halt weight drift, achieving both high performance and stability, in the case of uncertain payload and large unmeasured sinusoidal disturbance a situation where the common e-modification robust adaptive weight update cannot achieve a practical result.