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AssigneeSTMicroelectronics S.r.l.
InventorsPaolo Arena, Marco Branciforte, Giovanni Di Bernardo, Luigi Occhipinti
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A method of controlling the movements of a multi-actuator electromechanical system having a matrix of locally interconnected analog cells associated therewith is provided. Each cell represents a hardware implementation of a model of fuzzy inference rules. The model includes a fuzzy circuit architecture which may be implemented in an integrated circuit with VLSI CMOS technology that generates and controls a reaction diffusion mechanism typical of auto-waves using a fuzzy neural network. The fuzzy neural network defines the functional relationships that may duplicate simultaneous reaction diffusion equations. The duplication of the simultaneous reaction diffusion equations is provided using two sets of fuzzy rules processing, in a linguistic manner, the state variables of the cells. An oscillatory type dynamic is imposed on each cell where two dynamic processes having different kinetic characteristics coexist.
A programmable electronic circuit (1) for generating and controlling the movements of a multi-actuator electromechanical system, of the type associated with a cellular architecture comprising a plurality of programmable cells interconnected locally to provide a logic/mathematical representation of the locomotive phenomenon and a corresponding conversion of said representation to commands or electric pulses for driving a plurality of actuators associated with the cells, characterized by that it comprises a processing control unit (2) including a fuzzy type of electronic microcontroller.
A method of generating and controlling the movements of a multi-actuator electromechanical system, of the type providing a logic/mathematical representation of the locomotive phenomenon and a corresponding conversion of, said representation to commands or electric pulses through a cellular architecture being associated with a plurality of actuators, characterized by that said cellular architecture provides the resolution of fuzzy inference rules by updating said commands at each processing time according to the type of movement arranged for said actuators.
Dependencies are inferred from the claim text.