基于动力学模型预测控制的Stewart型轮足腿控制方法

To improve the motion precision and dynamics of Stewart type wheel-foot leg under variable posture, a dynamics model predictive control (MPC) was proposed. Firstly, the force analysis was carried out for Stewart platform and a dynamics model was derived with the Newton-Euler for state-space representation. Then, the MPC predictive model and cost function were established for optimization. Next, Adams and Matlab joint simulation was performed to regulate the MPC controller and evaluate its robustness to the un-modeled friction. Finally, the comparative experiments were conducted to verify the superiority of MPC controller to PI controller in terms of motion dynamics and precision under variable posture.