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      This paper develops a real-time, on-line gain tuning methodology for discrete-time Sliding mode control with Decoupled disturbance compensator and Auxiliary state (SDA) under control input saturation without pre-tests and offline tuning. The proposed methodology is implemented in industrial servo systems and the experiment results are presented in this paper. The discrete-time SDA method is a robust control method dependent on control input saturation and disturbances. However, when the gain parameter of the auxiliary state is improperly tuned, it is hard to achieve desired performance specifications due to oscillations or repeated occurrences of control input saturation. Previously, a gain tuning algorithm for the auxiliary state using pre-tests and offline tuning has been proposed. This paper extends this previous gain tuning algorithm and proposes a new algorithm which does not require pre-tests and offline tuning by predicting the maximum position error based on a given reference profile and the control hardware input limit. The developed algorithm is implemented and experimental results show the improvements in the tuning process without the time-consuming offline tuning procedure.
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      This paper develops a real-time, on-line gain tuning methodology for discrete-time Sliding mode control with Decoupled disturbance compensator and Auxiliary state (SDA) under control input saturation without pre-tests and offline tuning. The proposed ...

      This paper develops a real-time, on-line gain tuning methodology for discrete-time Sliding mode control with Decoupled disturbance compensator and Auxiliary state (SDA) under control input saturation without pre-tests and offline tuning. The proposed methodology is implemented in industrial servo systems and the experiment results are presented in this paper. The discrete-time SDA method is a robust control method dependent on control input saturation and disturbances. However, when the gain parameter of the auxiliary state is improperly tuned, it is hard to achieve desired performance specifications due to oscillations or repeated occurrences of control input saturation. Previously, a gain tuning algorithm for the auxiliary state using pre-tests and offline tuning has been proposed. This paper extends this previous gain tuning algorithm and proposes a new algorithm which does not require pre-tests and offline tuning by predicting the maximum position error based on a given reference profile and the control hardware input limit. The developed algorithm is implemented and experimental results show the improvements in the tuning process without the time-consuming offline tuning procedure.

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