This paper aims to analyse the system stability when decentralized adaptive controllers are applied to multi-input/multi-output non-linear interconnected systems. The local adaptive controllers are designed based on linear models by employing relative deadzones. Using a small-gain-type argument, we
On the robustness of adaptive controllers using relative deadzones
โ Scribed by R.H. Middleton; G.C. Goodwin; Y. Wang
- Publisher
- Elsevier Science
- Year
- 1989
- Tongue
- English
- Weight
- 522 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0005-1098
No coin nor oath required. For personal study only.
โฆ Synopsis
The szze of the unmodelled dynamtcs allowed by a robust adaptive control algorithm ts examined, and shown to be of the same order as that allowed by a hnear controller Key Words--Self-tumng control, convergence and stability problems m adaptwe control, robust adaptive control Absltrstt--Recently sutIicaent con&laons have been presented for robust stabthty of adapttve control aigonthms The purpose of this paper is to further examine these condmons, and to study the question of robustness and performance for adaptive and non-adaptive controllers In partEcular, we compare an adaptive controller with a fixed hnear controller for a representative system including structured and unstructured modelling errors In the case of unstructured modeihng errors alone, we show that the theoretical sufficient condmons for signal boundedness of the adaptive controller are comparable with those for the fixed hnear controller designed to achieve eqmvalent performance When structured modelhng errors (1 e parametric uncertainties) are added, then simulation studies of a second-order system suggest that the adaptive controller achieves superior performance to the fixed hnear controller *
๐ SIMILAR VOLUMES
In this paper we present a robust adaptive control scheme for robot manipulators with time-varying parameters and unmodeled dynamics. Our scheme ensures that all signals in the closed-loop robot system are bounded and the tracking error is of the order of the parameter variations and unmodeled dynam
This paper presents a design approach for discrete adaptive control systems which provides a quantitative measure of the effect of design alternatives such as (i) adaptive gain, (ii) model order, and (iii) sampling rate, on stability in the presence of unmodeled plant dynamics. The proposed method,
Combining the concept of persistent excitation with hybrid adaptation it is shown that any discrete-time adaptive system can be made robust in the presence of bounded perturbations.