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Volume 7 Issue 1
Jan.  2020

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Santanu Kumar Pradhan and Bidyadhar Subudhi, "Position Control of a Flexible Manipulator Using a New Nonlinear Self-Tuning PID Controller," IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 136-149, Jan. 2020. doi: 10.1109/JAS.2017.7510871
Citation: Santanu Kumar Pradhan and Bidyadhar Subudhi, "Position Control of a Flexible Manipulator Using a New Nonlinear Self-Tuning PID Controller," IEEE/CAA J. Autom. Sinica, vol. 7, no. 1, pp. 136-149, Jan. 2020. doi: 10.1109/JAS.2017.7510871

Position Control of a Flexible Manipulator Using a New Nonlinear Self-Tuning PID Controller

doi: 10.1109/JAS.2017.7510871
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  • In this paper, a new nonlinear self-tuning PID controller (NSPIDC) is proposed to control the joint position and link deflection of a flexible-link manipulator (FLM) while it is subjected to carry different payloads. Since, payload is a critical parameter of the FLM whose variation greatly influences the controller performance. The proposed controller guarantees stability under change in payload by attenuating the non-modeled higher order dynamics using a new nonlinear autoregressive moving average with exogenous-input (NARMAX) model of the FLM. The parameters of the FLM are identified on-line using recursive least square (RLS) algorithm and using minimum variance control (MVC) laws the control parameters are updated in real-time. This proposed NSPID controller has been implemented in real-time on an experimental set-up. The joint tracking and link deflection performances of the proposed adaptive controller are compared with that of a popular direct adaptive controller (DAC). From the obtained results, it is confirmed that the proposed controller exhibits improved performance over the DAC both in terms of accurate position tracking and quick damping of link deflections when subjected to variable payloads.


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    • Designed nonlinear self-tuning controller to control flexible-link manipulator.
    • Controller guarantees stability under change in payload.
    • Developed Nonlinear autoregressive moving average with exogenous-input model for manipulator.
    • Identified Parameters of manipulator on-line using RLS estimation.
    • Implemented the controller in real-time on an experimental set-up.


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