The hardware-in-the-loop (HIL) simulation is an important approach to test space robotic operations, rendering virtual free-floating dynamics on robotic facilities. However, this approach suffers from velocity divergence due to intrinsic time delay in the control loop. This paper proposes a passivity-based control strategy to handle the simulation divergence. A HIL simulation system with an industrial robot is modelled and its divergence problems are analyzed through numerical simulations. Then, through representing the HIL simulation system in a passivity network of view, the passivity observer (PO) of the dynamic system is established. The PO includes the effect of a real contact damping on energy flow of the passivity network during a contact process. Thus, a passivity controller is defined. Moreover, a real-time estimation method for contact damping is presented. Finally, collision experiments against a virtual wall and real collision experiments are both implemented. The experimental results show that the simulation divergence due to the time delay can be prevented by the proposed control strategy, and that the velocity characteristics with high fidelity are rendered on the HIL simulation system.
An industrial robot with a six-axis force/torque sensor is usually used to produce a zero-gravity environment for testing space robotic operations. However, using traditional force control methods, such as admittance control, causes position-controlled industrial robots to undergo from force divergence owing to intrinsic time delay. In this paper, a new force control method is proposed to eliminate the force divergence. A hardware-in-the-loop (HIL) simulator with an industrial robot is first presented. The free-floating satellite dynamics and the motion mapping from the satellites to simulator are both established. Thus, the effects of measurement delay and dynamic response delay on contact velocity and force are investigated. After that, a real-time estimation method for contact stiffness and damping is proposed based on the adaptive Kalman filter. The measurement delay is compensated by a phase lead model. Moreover, the identified contact parameters are adopted to modify contact forces, and thus the dynamics response delay can be compensated for. Finally, a co-simulation and experiments were conducted to verify the force control method. The results show that contact stiffness and damping could be identified exactly and that the simulation divergence could be prevented. This paper proposes an active compliance control method that can deal with force constrained tasks of a position-controlled robot in unknown environments.
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