Neural Network Adaptive Control for X-Y Position Platform with Uncertainty
Abstract: An improvement
neural network adaptive control strategy is put forward for X-Y position
platform with uncertainty by the paper. Firstly, dynamics model of X-Y position
platform is established. Then, RBF neural network with good learning ability is
used to approach non-linear system. The early period control accuracy of the
problem is considered by the paper, because good precision in the early period
is difficult to be obtained by neural network controller, so PID controller is
designed to compensate control. An improvement dynamic optimization adjustment
algorithm of network weights is designed to speed up the learning speed.
Simulation results show that the control method is more effective to improve
the control precision and real-time and has a good application value.
Author: Zhang Wenhui
Journal Code: jptkomputergg140026
