This work presents an integrated robust adaptive control scheme that merges the fuzzy control algorithm with the Cerebellar Model Arithmetic Control (CMAC) for unknown systems. The presented adaptation mechanism is used to tune the weight parameters in the CMAC, such that a given ideal stable controller will be best approximated without prior off-line learning phase required. A robust controlle...

Manipulator control is one of the main research areas in robotics, demanding for models with fast convergence and reliable stability for modelling and control. In this paper, the mechanisms of CMAC and ANFIS models for input space partitioning are analysed and their performance is compared to each other in terms of their abilities to model complex non-linear processes, with performance indexes ...

AbstructThe cerebellar model articulation controller (CMAC) neural network is a practical tool for improving existing nonlinear control systems. A typical simulation study is used to clearly demonstrate that the CMAC can effectively reduce tracking error, but can also destabilize a control system which is otherwise stable. Then quantitative studies are presented to search for the cause of insta...

Cerebellar Model Articulation Controller Neural Network is a computational model of cerebellum which acts as a lookup table. The advantages of CMAC are fast learning convergence, and capability of mapping nonlinear functions due to its local generalization of weight updating, single structure and easy processing. In the training phase, the disadvantage of some CMAC models is unstable phenomenon...

The Cerebellar Model Articulation Controller (CMAC) and fuzzy systems have been active areas of research since its initial introduction. Fuzzy CMAC is basically a CMAC that is coupled with a fuzzy system. This paper presents the incorporation of fuzzy systems into CMAC with Approximate Analogical Reasoning Scheme (AARS) as its inference rules and Discrete Incremental Clustering (DIC) as its tec...

With nonlinearity, large lag and time-varying model parameters of cement rotary kiln, this paper proposed a burning zone temperature control system of cement rotary kiln based on CMAC neural network. By Dynamic adjustment of PID controller parameters with CMAC neural network, combined with rotary kiln temperature control mechanism, the temperature controller based on CMAC-PID was designed. Then...

Under environments that the criteria to achieve a certain objective is unknown, the reinforcement learning is known to be effective to collect, store and utilize information returned from the environments. Without a supervisor, the method can construct criteria for evaluation of actions to achieve the objective. However, since the information received by a learning agent is obtained through an ...

Cerebellar Model Articulation Controller (CMAC) has some attractive features: fast learning capability and the possibility of efficient digital hardware implementation. Although CMAC was proposed many years ago, several open questions have been left even for today. Among them the most important ones are about its modelling and generalization capabilities. The limits of its modelling capability ...

We propose a Cerebellar Model Arithmetic Computer (CMAC) neural network for character recognition with an FPGA architecture. The CMAC has many advantages in terms of speed of operation based on LMS training. Its ability realizes arbitrary nonlinear mapping and fast practical hardware implementation. The CMAC, being a learning algorithm, can rapidly obtain output using nonlinear mapping with loo...

In this section we review the basic operating principles of the CMAC neural network as proposed by Albus [2,4-7]. We then present a mathematical description of the conventional CMAC in a form intended to facilitate software implementation. The notation used is somewhat different than in the original Albus papers, but the set of equations presented is numerically equivalent to the original Albus...