Extended filtering high‐gain output feedback controller for a class of uncertain nonlinear systems subject to external disturbances. (5th May 2020)

• Record Type: Journal Article
• Authors: Ma, Tong
• Other Names: Chen Jiming guestEditor.; Gupta Vijay guestEditor.; Quevedo Daniel E. guestEditor.; Tesi Pietro guestEditor.
• Is Part Of: International journal of robust and nonlinear control. Volume 30:Number 11(2020)
• Page Start: 4397
• Page End: 4417
• Publication Date: 2020-05-05
• Subjects: extended state observer (ESO) -- external disturbances -- high gain -- low‐pass filter -- uncertainty; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.4993
• Languages: English
• ISSNs: 1049-8923

Abstract

Abstract: In this article, an extended filtering high‐gain output feedback controller is developed for a class of uncertain nonlinear systems subject to external disturbances. The nonlinearities under consideration satisfy a semiglobal Lipschitz condition. The proposed control architecture integrates the extended state observer (ESO), high gain, and low‐pass filter together. None of them is used alone. The ESO can not only estimate the unknown internal state, but also deliver a good property of disturbance rejection simultaneously due to the presence of high gain. Since the high gain deteriorates the robustness of the system, a low‐pass filtering mechanism is added in the control law to filter away aggressive signals and recover the robustness. The filtering control law is designed to compensate the nonlinear uncertainties and deliver a good tracking performance with guaranteed stability. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. Since the virtual reference system defines the best performance that can be achieved by the closed‐loop system, the uniform performance bounds are derived for the states and control signals via comparison. Numerical examples are provided to illustrate the effectiveness of the novel design via comparisons with the model reference adaptive control method and L 1 adaptive controller.