
doi: 10.3934/mbe.2022588
pmid: 36654013
<abstract> <p>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.</p> </abstract>
model predictive control (MPC), Automated systems (robots, etc.) in control theory, inverse dynamics, hierarchical multiloop MPC scheme, Robotics, hierarchical multiloop mpc scheme, nonlinear disturbance observer (ndo), Feedback, model predictive control (mpc), Hierarchical systems, Nonlinear Dynamics, QA1-939, trajectory tracking, Computer Simulation, Model predictive control, Observers, TP248.13-248.65, Mathematics, nonlinear disturbance observer (NDO), Algorithms, Biotechnology
model predictive control (MPC), Automated systems (robots, etc.) in control theory, inverse dynamics, hierarchical multiloop MPC scheme, Robotics, hierarchical multiloop mpc scheme, nonlinear disturbance observer (ndo), Feedback, model predictive control (mpc), Hierarchical systems, Nonlinear Dynamics, QA1-939, trajectory tracking, Computer Simulation, Model predictive control, Observers, TP248.13-248.65, Mathematics, nonlinear disturbance observer (NDO), Algorithms, Biotechnology
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