基于扩张状态观测器和模型预测方法的四足机器人抗干扰复合控制

A novel composite control algorithm that combines the extended state observer, quadratic programming and model predictive control is proposed to improve the control performance of quadruped robot under model uncertainty and external disturbances. A model predictive controller is proposed for a quadruped robot based on the single rigid body model, and a variable bandwidth nonlinear extended state observer is developed to estimate the lumped disturbance, including the model mismatch and external forces. Based on the estimated result, a compensator is further constructed using the quadratic programming technique. The proposed control algorithm is validated through simulation. The simulated results demonstrate that the anti-disturbance composite controller is used to allow the robot to achieve the satisfactory control performance under the conditions of the changes in mass and the application of external forces. In comparison to existing studies, the proposed controller exhibits significant improvements in control accuracy and disturbance rejection capabilities.