Dynamic Linearization Based Adaptive Nonlinear Active Disturbance Rejection Control
Hui Yu, Ronghu Chi
Abstract
Hui Yu, Ronghu Chi
Abstract
This work deals with the control issue in disturbed discrete-time nonlinear nonaffine system. A novel adaptive nonlinear active disturbance rejection control based on dynamic linearization technique is designed. Through dynamic linearization technique, the nonlinear nonaffine system is translated into a linear parametric data model with a nonlinear uncertainty. The estimations of unknown parameter and the nonlinear uncertainty are proposed by using an adaptive law and an extended state observer, respectively. By considering parameter adaptation, the dynamics of reference trajectory, the uncertainty compensation, and nonlinear error feedback simultaneously, an adaptive nonlinear error feedback control law is proposed. The final simulations verify the practicability and the validity of the proposed control scheme.
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This work deals with the control issue in disturbed discrete-time nonlinear nonaffine system. A novel adaptive nonlinear active disturbance rejection control based on dynamic linearization technique is designed. Through dynamic linearization technique, the nonlinear nonaffine system is translated into a linear parametric data model with a nonlinear uncertainty. The estimations of unknown parameter and the nonlinear uncertainty are proposed by using an adaptive law and an extended state observer, respectively. By considering parameter adaptation, the dynamics of reference trajectory, the uncertainty compensation, and nonlinear error feedback simultaneously, an adaptive nonlinear error feedback control law is proposed. The final simulations verify the practicability and the validity of the proposed control scheme.
Key concepts: Control theory (sociology), Feedback linearization, Nonlinear system, Parametric statistics, Linearization, Adaptive control, Computer science, Trajectory