An adaptive Iterative Learning Control (ILC) algorithm based on an estimation procedure using a Kalman filter and an optimization of a quadratic criterion is presented. It is shown that by taking the measurement disturbance into consideration the resulting ILC filters become iteration varying. Results from experiments on an industrial robot show that the algorithm is successful also in an application.Keywords: Iterative learning control, disturbance rejection, synthesis, robot application
An adaptive Iterative Learning Control algorithm with experiments on an industrial robot
Mikael Norrlöf, IEEE MemberAbstract-An adaptive Iterative Learning Control (ILC) algorithm based on an estimation procedure using a Kalman filter and an optimization of a quadratic criterion is presented. It is shown that by taking the measurement disturbance into consideration the resulting ILC filters become iteration varying. Results from experiments on an industrial robot show that the algorithm is successful also in an application.
This letter gives an overview of classical iterative learning control algorithms. The presented algorithms are also evaluated on a commercial industrial robot from ABB. The presentation covers implicit to explicit model-based algorithms. The result from the evaluation of the algorithms is that performance can be achieved by having more system knowledge.
Closed loop identification of an industrial robot of the type ABB IRB 1400 is considered. Using data collected when the robot is subject to feedback control and moving around axis one linear black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities and it is found that the dynamics of the robot can be well approximated by a model consisting of three-masses connected by springs and dampers. It also found that the results of the identification depend on the properties of the input signal.
Keywords: identification, robotics, flexible arms
Closed Loop Identification of an Industrial Robot Containing FlexibilitiesMånsÖstring, Svante Gunnarsson * , Mikael Norrlöf
Department of Electrical Engineering, Linköping University, SE-58183 Linköping, Sweden
AbstractClosed loop identification of an industrial robot of the type ABB IRB 1400 is considered. Using data collected when the robot is subject to feedback control and moving around axis one linear black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities and it is found that the dynamics of the robot can be well approximated by a model consisting of three-masses connected by springs and dampers. It also found that the results of the identification depend on the properties of the input signal.
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