Adaptive Robust Tracking Control for Hybrid Models of Three-Dimensional Bipedal Robotic Walking Under Uncertainties
Adaptive Robust Tracking Control for Hybrid Models of Three-Dimensional Bipedal Robotic Walking Under Uncertainties
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DOI：
10.1115/1.4050259
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发表时间：
2021-08
影响因子：
1.7
通讯作者：
Yan Gu;C. Yuan
中科院分区：
文献类型：
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作者：
Yan Gu;C. Yuan
介绍了一种自适应鲁棒轨迹跟踪控制器设计，可有效地实现两足机器人在参数化和未建模不确定性条件下的稳定行走。由于高度复杂的双足步行动力学是混合的，并且涉及非线性、不受控制的状态触发跳跃，因此推导这样的控制器是具有挑战性的。本研究的主要贡献是通过将多个Lyapunov函数的构造引入到控制Lyapunov函数中，合成了两足机器人混合行走模型的连续相位自适应鲁棒跟踪控制律。明确地分析了Lyapunov函数在状态触发跳跃上的演化，以构建指导所提出的控制设计的充分条件，以证明在存在不确定性的情况下保证混合系统的稳定性和跟踪性能。对全驱动双足机器人行走的仿真结果验证了该方法在不确定条件下行走稳定的有效性。
This paper introduces an adaptive robust trajectory tracking controller design to provably realize stable bipedal robotic walking under parametric and unmodeled uncertainties. Deriving such a controller is challenging mainly because of the highly complex bipedal walking dynamics that are hybrid and involve nonlinear, uncontrolled state-triggered jumps. The main contribution of the study is the synthesis of a continuous-phase adaptive robust tracking control law for hybrid models of bipedal robotic walking by incorporating the construction of multiple Lyapunov functions into the control Lyapunov function. The evolution of the Lyapunov function across the state-triggered jumps is explicitly analyzed to construct sufficient conditions that guide the proposed control design for provably guaranteeing the stability and tracking the performance of the hybrid system in the presence of uncertainties. Simulation results on fully actuated bipedal robotic walking validate the effectiveness of the proposed approach in walking stabilization under uncertainties.