Flexible Two-wheeled Self-balancing Robot Control Based on Hopfield Neural Network

Real control of robot is realized successfully by using spring to imitate the lumbar of human-being and adopt-ing LQR(linear quadratic regulator).For posture control of the flexible two-wheeled self-balancing robot,a kind of discrete Hopfield network way based on associative study is presented,and self-adaptive and self-organizing posture control is accom-plished in a manner of biological control.Firstly,a reasonable energy function is defined for the nonlinear,strong coupling and flexible robot system.Then,a Hopfield neural network controller suitable for this dynamic process is designed based on the dynamics equation of the flexible robot,and its convergence is analyzed.Simulation experiments show the effectiveness of the method and prove the stability of the system.The rationality and availability of the system posture controller design are indicated through analyzing the experiment results in detail.