A stochastic approach to fuzzy control

Abstract

The paper presents the utilization of low-resolution data for control purposes. The control is based on fuzzy logic, with the deployment of stochastic digital low-resolution time arrays. Every control decision contains a degree of imprecision, being derived from measured low-resolution data. The imprecision is eliminated by stochastic noise superimposed during the data gathering, while the negative effects of noise are suppressed both by the fuzzy nature of the decision-making process and by the energy inertia in the controlled object. The proposed stochastic fuzzy control is extremely fast, robust and so simple that it practically does not need a microprocessor. This approach is validated by a simulation of holding upright an inverse pendulum.