Additive-Decomposition-Based Output Feedback Tracking Control for Systems with Measurable Nonlinearities and Unknown Disturbances

TL;DR

This paper introduces an additive-decomposition-based control scheme that effectively manages output feedback tracking, disturbance rejection, and stabilization for nonlinear systems with measurable nonlinearities and unknown disturbances, combining time and frequency domain design.

Contribution

It proposes a novel additive decomposition approach that separates tracking, rejection, and stabilization tasks, enhancing performance and robustness in nonlinear control systems.

Findings

Successfully applied to a single-link robot arm with sinusoidal disturbances

Combines transfer function and backstepping methods for improved control

Demonstrates effective disturbance rejection and tracking performance

Abstract

In this paper, a new control scheme, called as additive-decomposition-based tracking control, is proposed to solve the output feedback tracking problem for a class of systems with measurable nonlinearities and unknown disturbances. By the additive decomposition, the output feedback tracking task for the considered nonlinear system is decomposed into three independent subtasks: a pure tracking subtask for a linear time invariant (LTI) system, a pure rejection subtask for another LTI system and a stabilization subtask for a nonlinear system. By benefiting from the decomposition, the proposed additive-decomposition-based tracking control scheme i) can give a potential way to avoid conflict among tracking performance, rejection performance and robustness, and ii) can mix both design in time domain and frequency domain for one controller design. To demonstrate the effectiveness, the output feedback tracking problem for a single-link robot arm subject to a sinusoidal or a general disturbance is solved respectively, where the transfer function method for tracking and rejection and backstepping method for stabilization are applied together to the design.