Learning control for position tracking of active suspension of high-speed AGV via neural network

This paper proposes a position tracking control approach of AGV´s platform using neural network The control problem of AGV´s active suspension is first analysed. Then a neural network control scheme for controlling active suspension is presented. The controller adopts a multilayer back-propagation neural network To obtain the fastest possible speed of convergence and to meet the need of real-time control, a prediction-correction method for adjusting learning parameters is developed. Finally, various manoeuvres of the AGV are simulated to evaluate the performance of the controller. The simulation results indicate that the neural network control scheme is feasible. The neuro-controller can accommodate the variation of operational conditions and environment