Layered control of forklift lateral stability based on Takagi–Sugenofuzzy neural network

Abstract

An anti-roll hydraulic cylinder is designed as an executive mechanism of the lateral stability control to provide lateral support force on the basis of an analysis of the structure of the forklift and the mechanism of lateral instability. A lateral stability layered control method based on Takagi–Sugeno (T–S) fuzzy neural network is proposed, divides the forklift lateral stability control into the upper identification layer, the middle control layer and the lower executive layer. Simulation and real vehicle test results indicate that the forklift lateral stability control method based on the T–S fuzzy neural network can effectively identify the forklift driving state, reduce the forklift rollover possibility and improve forklift safety under limited working conditions.