As an innovative concept, an optimal predictive impedance controller (OPIC) is introduced here to control a lower limb rehabilitation robot (LLRR) in the presence of uncertainty. The desired impedance law is considered to propose a conventional model-based impedance controller for the LLRR. However, external disturbances, model imperfection, and parameters uncertainties reduce the performance of the controller in practice. In order to cope with these uncertainties, an optimal predictive compensator is introduced as a solution for a proposed convex optimization problem, which is performed on a forward finite-length horizon. As a result, the LLRR has the desired behavior even in an uncertain environment. The performance and efficiency of the proposed controller are verified by the simulation results.

作为一个创新概念，此处引入了最佳预测阻抗控制器（OPIC），在存在不确定性的情况下控制下肢康复机器人（LLRR）。期望的阻抗定律被认为为LLRR提出了一种基于模型的常规阻抗控制器。但是，外部干扰，模型缺陷和参数不确定性实际上会降低控制器的性能。为了应对这些不确定性，引入了最佳预测补偿器作为提出的凸优化问题的解决方案，该问题在正向有限长度水平线上执行。结果，即使在不确定的环境中，LLRR也具有所需的行为。仿真结果验证了所提出控制器的性能和效率。