Disturbance Rejection Performance of Adaptive Robust Control

Achieving high control performance in the presence of unavoidable disturbances/uncertainties has always been a major objective in modern control design. These disturbances/uncertainties may cause the controlled system, designed on the nominal model, to be unstable or have a much degraded performance. To deal with the disturbances/uncertainties, disturbance-observer-base-controls construct observers to estimate the disturbance and then compensate their influences. Among them, active disturbance rejection control (ADRC) takes all disturbances and uncertainties as total disturbances and then constructs an extended state observer to estimate the these disturbances. The simplicity and independence on precise model make ADRC one of the popular control algorithms in recent years. From another prospect, the mathematically rigorous adaptive robust control (ARC) is proposed, where the model uncertainties are classified into parametric uncertainties and uncertain nonlinearities and handled by integrating the working mechanisms of two of the main control research areas - robust adaptive control and nonlinear robust controls. The ARC theory has also been applied to the design of various intelligent and precision industrial mechatronic systems. In this paper, the disturbance rejection performance of ARC is studied with the comparison with ADRC. First-order nonlinear system with disturbance/uncertainties is studied as an example and simulations are conducted to support the comparative results.