This paper proposes an adaptive TS recurrent fuzzy CMAC (TS-RFCMAC) model based control of uncertain time-delay nonlinear systems. First, we introduce a TS-RFCMAC network and its application on system modeling. Next, a TS-RFCMAC controller is developed based on parallel distributed compensation and adaptive control laws. Even if uncertain local subsystem matrices and fuzzy sets exist in the mod...

An adaptive dynamic balance scheme was implemented and tested on an experimental biped. The control scheme used pre-planned but adaptive motion sequences. CMAC neural networks were responsible for the adaptive control of side-to-side and front-to-back balance, as well as for maintaining good foot contact. Qualitative and quantitative test results show that the biped performance improved with ne...

Status of This Memo This document specifies an Internet standards track protocol for the Internet community, and requests discussion and suggestions for improvements. Please refer to the current edition of the "Internet Official Protocol Standards" (STD 1) for the standardization state and status of this protocol. Distribution of this memo is unlimited. Abstract Some implementations of IP Secur...

In this paper, we first present a new distinguisher on the CBC-MAC based on a block cipher in Cipher Block Chaining (CBC) mode. It can also be used to distinguish other CBC-like MACs from random functions. The main results of this paper are on the secondpreimage attack on CBC-MAC and CBC-like MACs include TMAC, OMAC, CMAC, PC-MAC and MACs based on three-key encipher CBC mode. Instead of exhaust...

CMAC (Albus, 1975b) is well known as a good function approximator with local generalization abilities. Depending on the smoothness of the function to be approximated, the resolution as the smallest distinguishable part of the input domain, plays a crucial role. If the usually used binary quantizing functions are dropped in favor of more general, continuous-valued functions, this drawback can be...

This report describes a series of results using the exponentiated gradient descent (EG) method recently proposed by Kivinen and Warmuth. Prior work is extended by comparing speed of learning on a nonstationary problem and on an extension to backpropagation networks. Most signi cantly, we present an extension of the EG method to temporal-di erence and reinforcement learning. This extension is co...

The network and plant can be regarded as a controlled time-varying system because of the random induced delay in the networked control systems. The cerebellar model articulation controller CMAC neural network and a PD controller are combined to achieve the forward feedback control. The PD controller parameters are adjusted adaptively by fuzzy reasoning mechanism, which can optimize the control ...