Hierarchical multiloop MPC scheme for robot manipulators with nonlinear disturbance observer

Xingjia Li; Jinan Gu; Zedong Huang; Chen Ji; Shixi Tang; Xingjia Li; Jinan Gu; Zedong Huang; Chen Ji; Shixi Tang

doi:10.3934/mbe.2022588

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 12: 12601-12616. doi: 10.3934/mbe.2022588

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Research article

Hierarchical multiloop MPC scheme for robot manipulators with nonlinear disturbance observer

1.
School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China
2.
School of Information Engineering, Yancheng Teachers University, Yancheng 224002, China

Academic Editor: Vladimir Mityushev

Received: 30 June 2022 Revised: 14 August 2022 Accepted: 16 August 2022 Published: 29 August 2022

This paper addresses the robust enhancement problem in the control of robot manipulators. A new hierarchical multiloop model predictive control (MPC) scheme is proposed by combining an inverse dynamics-based feedback linearization and a nonlinear disturbance observer (NDO) based uncertainty compensation. By employing inverse dynamics-based feedback linearization, the multi-link robot manipulator was decoupled to reduce the computational burden compared with the traditional MPC method. Moreover, an NDO was introduced into the input torque signal to compensate and correct the errors from external disturbances and uncertainties, aiming to enhance the robustness of the proposed controller. The feasibility of the proposed hierarchical multiloop MPC scheme was verified and validated via simulation of a 3-DOF robot manipulator. Results demonstrate that the proposed controller provides comparative accuracy and robustness and extends the existing state-of-the-art algorithms for the trajectory tracking problem of robot manipulators with disturbances.
- trajectory tracking,
- inverse dynamics,
- model predictive control (MPC),
- nonlinear disturbance observer (NDO),
- hierarchical multiloop MPC scheme
Citation: Xingjia Li, Jinan Gu, Zedong Huang, Chen Ji, Shixi Tang. Hierarchical multiloop MPC scheme for robot manipulators with nonlinear disturbance observer[J]. Mathematical Biosciences and Engineering, 2022, 19(12): 12601-12616. doi: 10.3934/mbe.2022588

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Abstract

This paper addresses the robust enhancement problem in the control of robot manipulators. A new hierarchical multiloop model predictive control (MPC) scheme is proposed by combining an inverse dynamics-based feedback linearization and a nonlinear disturbance observer (NDO) based uncertainty compensation. By employing inverse dynamics-based feedback linearization, the multi-link robot manipulator was decoupled to reduce the computational burden compared with the traditional MPC method. Moreover, an NDO was introduced into the input torque signal to compensate and correct the errors from external disturbances and uncertainties, aiming to enhance the robustness of the proposed controller. The feasibility of the proposed hierarchical multiloop MPC scheme was verified and validated via simulation of a 3-DOF robot manipulator. Results demonstrate that the proposed controller provides comparative accuracy and robustness and extends the existing state-of-the-art algorithms for the trajectory tracking problem of robot manipulators with disturbances.

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