Considering the problem of grasping using multifingered robot hand in its dynamics and control integrity requires the analysis and control of a high dimensional, nonlinear complex system with time varying parameters and incorporating uncertainty. Such complex control system operating in unstructured environments will naturally involve the handling and fusion of information with different types of uncertainties. Decentralized control rises as an alternative to complicated global control since it involve dynamics at a lower dimension locally, thus generating easier analysis. There, global uncertainty becomes fragmented into local lower dimensional uncertainty at each of the smallest control units. Consequently, the complex global problem of grasping with a robot hand is transformed into smaller control units communicating between each other while uncertainty is propagated. The aims of this project is to develop such a decentralized control model and to apply it to a grasping problem. The completed phases of this project are: * Modelling uncertainty * Generating the cellular control space * Developing a cellular control scheme * Applying it to a robot hand control problem. Within the frame work of this project three methodologies were developed and tested in a Robot environment: * Fuzzy Cell to Cell Mapping and its application to turning a Fuzzy Controller. * Fuzzy Dynamic Programming and its application to grasping with a Robot Hand. * Fractal Intelligent Network and its applications to sensorimotor control of a robot hand.