This paper presents a new intelligent PID tuning scheme, whose PID tuner is constructed by the fusional structure of a cerebellar model articulation controller and a neural network.
This paper presents an intelligent control scheme that uses a cerebellar model articulation controller (CMAC) and genetic algorithms (GA) in aircraft automatic landing control and to make automatic landing systems (ALS) more intelligent.
This paper presents an approach to rotor position estimation in switched reluctance motors (SRMs) by using a cerebellum model articulation controller (CMAC).
This study presents a cerebellar model articulation controller NN (CMAC NN) classifier, which has the advantages of very fast learning, reasonable generalization ability and robust noise resistance.
Albus also formulated his version as a software algorithm he called a CMAC (Cerebellar Model Articulation Controller), which has been tested in a number of applications.
This is implemented, based on the availability of training data set and requirement of in-time performance, by an adaptive cerebellar model articulation controller neural network, a finite state machine, a fuzzy controller and purposely designed gesture recognition and control command generation systems.
In addition, a fuzzy cerebellar model articulation controller (FCMAC) neural network is used to guarantee controller robustness to uncertainties.
In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems.
In this study, we apply a self-organizing cerebellar model articulation controller (SOCMAC) network to design an ECG classifier by observing the QRS complex of each heartbeat.
