Robust control of a mobile inverted pendulum robot using a RBF neural network controller

This article presents robust control of the mobile inverted pendulum system(MIPS) whose structure is a combination of a wheeled mobile robot and an inverted pendulum with two arms. The MIPS navigates on the horizontal plane while balancing the pendulum. Control of the MIPS is difficult since the system is non-holonomic and nonlinear so that simple linear controllers may have poor performances for the system. The radial basis function(RBF) network is used as an auxiliary controller to help the primary PID controllers to perform better. The back propagation algorithm has been developed for the RBF function network. Real time control of the RBF network has been achieved by embedding the learning algorithm onto the DSP board. The performance of the RBF network controller has been tested for the remotely controlled MIPS by conducting experiments of climbing the slanted surface while balancing.