Latest Papers

ASME Journal of Mechanisms and Robotics

  • Stable Inverse Dynamics for Feedforward Control of Nonminimum-Phase Underactuated Systems
    on January 25, 2023 at 12:00 am

    AbstractAn enhanced inverse dynamics approach is here presented for feedforward control of underactuated multibody systems, such as mechanisms or robots where the number of independent actuators is smaller than the number of degrees of freedom. The method exploits the concept of partitioning the independent coordinates into actuated and unactuated ones (through a QR-decomposition) and of linearly combined output, to obtain the internal dynamics of the nonminimum-phase system and then to stabilize it through proper output redefinition. Then, the exact algebraic model of the actuated sub-system is inverted, leading to the desired control forces with just minor approximations and no need for pre-actuation. The effectiveness of the proposed approach is assessed by three numerical test cases, by comparing it with some meaningful benchmarks taken from the literature. Finally, experimental verification through an underactuated robotic arm with two degrees of freedom is performed.

Self-Identification of Cable-Driven Exoskeleton Based on Asynchronous Iterative Method


The upper limb rehabilitation exoskeleton with cable-driven parallel structure has the advantages of light weight and large payload, etc. However, due to the non-rigid nature of the actuating cables and the different body shape of the wearer, the geometric parameters of the exoskeleton have a large error. The parameter identification of cable-driven exoskeleton is of great significance. An asynchronous self-identification method for the upper limb seven degree-of-freedom (DOF) cable-driven exoskeleton was proposed and used in a wearable multi-redundant exoskeleton. Asynchronous iteration eliminates the accumulation of joint errors. High identification reliability is achieved by selecting proper identification parameters and optimizing error model.With the method, the geometric parameters of the exoskeleton can be identified by using exoskeleton joint angle and cable length data. The experiment verifies that the success rate of parameter identification for different wearers is in line with expectations, and the control precision and stability of the prototype are greatly improved after parameter identification.

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