Point stabilization control for two-wheel robot with online parameters settings

Abstract

For the model time varying during point stabilization control of two-wheel robot with nonholonomic constraint, velocity, and acceleration limit, this paper proposes a multi-mode proportion control approach based on neural network. The point stabilization intelligence control is achieved by optimizing the multi-mode human simulated intelligence control(HSIC) controller with BP neural network online learning. With the performance variation of robot motion execution system, the simulation results compare the approach we proposed with the proportion controller and proportion cosine controller. The validity of the approach is confirmed in the simulation.