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Abstract
Iterative learning control is a controlling tool developed to overcome periodic disturbances acting on repetitive systems. State-feedback ILC controller was designed based on the use of the small gain theorem. Stability conditions were reported in the case of past error and current error feedback schemes based on Singular values. Disturbances acting on the load of the system were reported for the case of past error feedforward only which kept the investigation of the current error feedback as an open question. This paper develops a comparison between the past error feedforward and current error feedback schemes disturbance conditions in singular values. As a result, the conditions found highly support the use of the past error over the current error feedback.
Highlights
Robot manipulators can be provided to undertake a pick and place operation with repeated executions of a finite duration task
Stability conditions were reported in the case of past error and current error feedback schemes based on Singular values
This paper develops a comparison between the past error feedforward and current error feedback schemes disturbance conditions in singular values
Summary
Robot manipulators can be provided to undertake a pick and place operation with repeated executions of a finite duration task. An object is collected from a fixed location point, transferred with predefined period to be placed at another specified location. The robot returns to the starting location point to repeat the same task repeatedly. The objective is to follow a prescribed reference as closely as possible for as many times as possible before the need for resetting. Other applications arise having the same operation manner, such as chemical batch processes, petrochemical processes, and microelectronics manufacturing [1].
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