仿人预测控制在双足机器人步行控制中的应用

Application of human-simulated predictive control in walking control of biped robot

基于零力矩点(ZMP)的预测控制是目前双足机器人步行控制中最先进的方法,但是预测控制需要比较精确的预测模型,在环境扰动导致模型失配时,预测控制的性能下降较快。为了解决这个问题,利用仿人智能控制对环境误差具有较强抑制的特点改进预测控制。探讨了在步行控制中引入仿人智能控制的必要性和仿人智能控制改进预测控制的可行性,并设计了仿人预测控制器。最后通过仿真实验验证了新的控制器对双足机器人步行控制的有效性。

Now predictive control based on zero moment point（ ZMP） is the most advanced walking control method for biped robot,but predictive control need more accurate predictive model,and performance of predictive control declines rapidly when environmental perturbation resulting in model mismatch.In order to solve this problem,the predictive control can be improved by using the characteristics of human-simulated intelligent con- trol（ HSIC） has strong ability to suppress environment error.The necessity is discussed of introducing HSIC into walking control,and the feasibility of improving predictive control by using HSIC,then design human-simulated predictive controller.Finally,simulation experiments verify the effectiveness of new controller on walking control of biped robot.