Design of a fuzzy logic adaptive optimal robust controller for a ball-riding robot

Ball-riding robot is fascinated to humans because of its characteristic. Euler-Lagrange is used to describe the robot dynamics. By including the actuating motor dynamics into the robot equation, robot precise dynamics model can be obtained. The real robot is implemented by using acrylic and aluminum. Robot is controlled by using ARM-Cortex M3 embedded controller. Inertia moment unit information is fused and used to obtain robot's leaning angles. The adaptive optimal robust controller is introduced and proved to satisfy the necessary robot balancing conditions. Fuzzy Logic controller is selected as the adaptive part of the proposed controller. The robot model is simulated with parameter uncertainty and in noisy environments. The control algorithm is implemented to nonlinear model of the robot in order to achieve robot stability. The proposed controller is simulated in present of uncertainty.