This article presents a novel robust centralized controller for impedance control and reference tracking of redundant manipulators. The proposed approach takes advantage of the robustness properties of sliding mode control (SMC) and the prediction capabilities of model predictive control (MPC). SMC theory is employed to compensate unmodeled system dynamics and disturbances, ensuring accurate tracking and enforcement of a desired end-point impedance during interaction with the environment. Differently from other schemes, the sliding manifold is expressed directly in the task space and the approach is generalized to redundant manipulators by projection of the manifolds into joint space. Chattering attenuation is provided by a second-order integral sliding mode control law. These features are exploited by the MPC to guarantee motion and actuation constraint fulfillment based on the nominal feedback linearized robot model. A formal analysis of the control system is given along with the relevant proofs. The resulting model predictive sliding mode controller is able to cope with delays acting on the control input torque. The effectiveness of the approach is validated in simulation on a 4-DOF planar robot, and its viability on real platforms through experiments on a 7-DOF prototype ABB YuMi robot arm.

中文翻译：

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冗余机械手的操作空间模型预测滑模控制

本文提出了一种新颖的鲁棒集中控制器，用于冗余机械手的阻抗控制和参考跟踪。所提出的方法利用了滑模控制 (SMC) 的鲁棒性和模型预测控制 (MPC) 的预测能力。SMC 理论用于补偿未建模的系统动态和干扰，确保在与环境交互期间准确跟踪和执行所需的端点阻抗。与其他方案不同的是，滑动流形直接在任务空间中表达，并且通过将流形投影到关节空间，将该方法推广到冗余操纵器。颤振衰减由二阶积分滑模控制律提供。MPC 利用这些特征来保证基于标称反馈线性化机器人模型的运动和驱动约束满足。给出了控制系统的形式分析以及相关证明。由此产生的模型预测滑模控制器能够处理作用于控制输入扭矩的延迟。该方法的有效性在 4 自由度平面机器人的仿真中得到验证，并通过 7 自由度原型 ABB YuMi 机器人手臂的实验在真实平台上得到验证。