Adaptive control system for multiple micro-machines

In this paper, the design of an adaptive control system architecture for multiple micro-machines has been proposed. The architecture is made up two parts: one is various numeric values from micro-machines represented by a possibility distribution and kept as the micro states, and they are produced as the macro states by a combination mechanism and are recalled a group´s behavior of micro-machines from memory by a bidirectional associative memory; and the other one, the macro states are compared with this system scenario, and the most adaptive scenario is selected by a fuzzy integral using a fuzzy measure so that the plan can be changed to a new concrete plan by genetic algorithm. Although this system has been developing, the preliminary study on this has proved that it was significantly useful for new application of micromachines control