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> 0.96), and low cost (power consumption: 5 mW, preparation cost <CNY 100). The proposed force controller for the soft gripper was designed based on the Hammerstein nonlinear model, and due to adaptive laws designed by an adaptive theory and the full online sequential extreme learning machine, respectively, its parameters can be adjusted online. The simulation and experiment results demonstrate that the proposed force controller exhibits good force control performance and robustness in a nonlinear contact environment. Moreover, because of its simple control structure and good online learning ability, the proposed controller has the advantages of being real time and easy to realize, which shows its potential applications in many grasping tasks, such as collecting biological samples and sorting industrial products.
Yang et al. (Thu,) studied this question.
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