In this paper, a novel hybrid optimal Adaptive High-Order Super Twisting Sliding Mode (AHOSTWSM) impedance control is proposed for a lower limb exoskeleton robot with 7 active joints, which takes the interaction forces between the robot and the user into account. First, the dynamic model of the robot is extracted using Lagrange approach. Then, an adaptive super twisting sliding mode controller is designed based on Lyapanov theory. Moreover, the interaction forces are obtained in every time-step and applied to the robot as a compensating torque to guard against disturbances. The desired trajectory of the upper limb joint has been extracted so that the stability of the robot is achieved based on Zero Moment Point (ZMP) criterion at any moment. Moreover, to achieve optimal performance (maximum stability, minimum tracking error, reduced interacting forces, and optimal energy consumption), parameters of the proposed controller, the upper limb desired trajectory, and the impedance system are optimized using Harmony Search Algorithm (HSA). Finally, in order to demonstrate the effectiveness of the proposed controller, optimal sliding mode controller (SMC) is designed and performance of the AHOSTWSM is compared with SMC. The simulation results reveal the superiority of the controller in comparison with SMC.

本文针对具有7个活动关节的下肢外骨骼机器人，提出了一种新型的混合最优自适应高阶超扭曲滑模（AHOSTWSM）阻抗控制，其中考虑了机器人与用户之间的相互作用力。首先，使用拉格朗日方法提取机器人的动力学模型。然后，基于Lyapanov理论设计了一种自适应超扭曲滑模控制器。此外，在每个时间步长都获得了相互作用力，并将其作为补偿扭矩施加到机器人上，以防止干扰。提取了上肢关节的期望轨迹，从而可以随时基于零力矩点（ZMP）标准实现机器人的稳定性。此外，为了获得最佳性能（最大稳定性，最小跟踪误差，减小的相互作用力和最佳的能量消耗），使用和谐搜索算法（HSA）对所提出的控制器的参数，上肢期望的轨迹和阻抗系统进行优化。最后，为了证明所提出的控制器的有效性，设计了最佳滑模控制器（SMC），并将AHOSTWSM的性能与SMC进行了比较。仿真结果表明，该控制器与SMC相比具有优越性。