This thesis considers the use of optimal techniques within iterative learning control (ILC) applied to linear systems. Two different aspects are addressed: the first is the duality relationship existing between iterative learning control and repetitive control which allows the synthesis of controllers developed in one domain to be applied in the other. Significant extensions to existing duality framework are made by eliminating an explicit current-error feedback loop and providing the facility of both current error feedback, and previous error feedforward within the control structure. This, in turn, with the case when either state-feedback or output-feedback is used to solve the ILC control paradigm extends the range of underlying plants to...
Abstract In this thesis a set of new algorithms is introduced for Iterative Learning Control (ILC) a...
Error convergence in Iterative Learning Control (ILC) is generally highly dependent on the selection...
Iterative learning control (ILC) has been intensely researched for over 30 years to improve the perf...
This thesis considers the use of optimal techniques within iterative learning control (ILC) applied ...
This thesis concerns the general area of experimental benchmarking of Iterative Learning Control (IL...
This thesis concerns the general area of experimental benchmarking of Iterative Learning Control (IL...
Repetitive processes are widespread in our world. Through repetition performance can be improved. A ...
A duality has been shown to exist between iterative learning and repetitive control, in which both c...
This thesis concerns the implementation and comparison of different Iterative Learning Control (ILC)...
© 2019 Dr. Gijo SebastianIterative learning control (ILC) is an advanced control algorithm that achi...
Iterative learning control (ILC) algorithms are employed in many applications, especially these invo...
This dissertation presents a series of new results of iterative learning control (ILC) that progress...
In this thesis a new robustness analysis for model-based Iterative Learning Control (ILC) is present...
In this thesis a new robustness analysis for model-based Iterative Learning Control (ILC) is present...
Industrial robots are widely used in industry because of their dexterity, the high manipulation spee...
Abstract In this thesis a set of new algorithms is introduced for Iterative Learning Control (ILC) a...
Error convergence in Iterative Learning Control (ILC) is generally highly dependent on the selection...
Iterative learning control (ILC) has been intensely researched for over 30 years to improve the perf...
This thesis considers the use of optimal techniques within iterative learning control (ILC) applied ...
This thesis concerns the general area of experimental benchmarking of Iterative Learning Control (IL...
This thesis concerns the general area of experimental benchmarking of Iterative Learning Control (IL...
Repetitive processes are widespread in our world. Through repetition performance can be improved. A ...
A duality has been shown to exist between iterative learning and repetitive control, in which both c...
This thesis concerns the implementation and comparison of different Iterative Learning Control (ILC)...
© 2019 Dr. Gijo SebastianIterative learning control (ILC) is an advanced control algorithm that achi...
Iterative learning control (ILC) algorithms are employed in many applications, especially these invo...
This dissertation presents a series of new results of iterative learning control (ILC) that progress...
In this thesis a new robustness analysis for model-based Iterative Learning Control (ILC) is present...
In this thesis a new robustness analysis for model-based Iterative Learning Control (ILC) is present...
Industrial robots are widely used in industry because of their dexterity, the high manipulation spee...
Abstract In this thesis a set of new algorithms is introduced for Iterative Learning Control (ILC) a...
Error convergence in Iterative Learning Control (ILC) is generally highly dependent on the selection...
Iterative learning control (ILC) has been intensely researched for over 30 years to improve the perf...