Advances in engineering research/Advances in Engineering Research · 2015 · 10 citations · 0 references
EngineeringComputer ScienceArtificial IntelligenceMachine LearningProcess ControlAdaptive ControlControl System DesignControl SystemsControl TheoryMotion ControlNeural NetworksAdaptive Neural ControlControl System RobustnessFault Tolerance MechanismsIntelligent ControlMotion Control SystemsNeural Network ControlRobustness
Artificial neural network is composed by a large number of processing interconnected unit. It is a nonlinear, adaptive information processing system. It has self-organizing, adaptive and self-learning ability. And can be used to calculate complex relationship between input and output, thus it has effective control ability. Rubber is the main material in the process of the mixer. It has a great influence on the final product. But at present many factories are added in the rubber by manual control. So this article takes the rubber transport equipment as the object, establish a BP neural network intelligent control system, using neural network self-learning ability and the adaptive ability to deal with uncertain information, to solve the problem of motion control of multiple dynamic input. Through the test of practical application, the system has strong robustness, adaptability, good generality and fault tolerance.