Dual-Stage Iterative Learning Control for MIMO Mismatched System With Application to Robots With Joint Elasticity

This paper discusses the tracking control problem for a class of multi-input-multi-output mismatched systems, where there are disturbances in different channels from the control input and the real-time feedback signal is not the output of interest. These mismatched issues make it difficult to achieve high tracking performance for the output of interest. To address this problem, two model-based iterative learning control (ILC) algorithms, namely reference ILC and torque ILC, are designed for different injection locations in the closed-loop system. An ad hoc hybrid scheme is proposed to make transitions between the two ILC stages for them to work properly at the same time. The application to both single-joint and multi-joint robots with joint elasticity are discussed with complete dynamic modeling and state estimation method for desired learning, as well as the extensive experimental validations on both systems.