Application of the Smith-Åström Predictor to robot force control

Input/output transport delay is prevalent in process control, causing performance degradation and even instability. This paper focuses on input and measurement delays in robot force control with stiff environments which tend to be susceptible to modeling error and disturbances. Traditional remedies include increasing the sampling rate, adding passive compliance, or modifying the feedback algorithm, e.g., using integral force feedback instead of proportional feedback. For force control using industrial robots, the problem is even more severe, as the loop closure is done at the outer kinematic loop through setpoint modification, which typically has long actuation latency, in addition to force measurement delay. In this paper, we apply two types of delay compensation to force control for a spring-type environment via direct cancellation: Smith Predictor, and its variant Åström Predictor. We show through simulation, and experimental validation on an industrial robot arm, that both methods significantly improve the stability margin as compared to the typical integral force control, with the Åström Predictor further improving the dynamical response by decoupling delay compensation and tracking response.