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Adaptive state‐feedback control with sensor failure compensation for asymptotic output tracking
Author(s) -
Song Ge,
Tao Gang
Publication year - 2019
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2958
Subject(s) - control theory (sociology) , compensation (psychology) , adaptive control , tracking (education) , control engineering , computer science , scheme (mathematics) , matching (statistics) , signal (programming language) , tracking error , state (computer science) , control (management) , controller (irrigation) , fault detection and isolation , engineering , mathematics , actuator , artificial intelligence , algorithm , agronomy , biology , psychology , mathematical analysis , pedagogy , statistics , psychoanalysis , programming language
Summary This paper addresses a new adaptive output tracking problem in the presence of uncertain plant dynamics and uncertain sensor failures. A new unified nominal state‐feedback control law is developed to deal with various sensor failures, which is directly constructed by state sensor outputs. Such a new state‐feedback compensation control law is able to ensure the desired plant‐model matching properties under different failure patterns. Based on the nominal compensation control design, a new adaptive compensation control scheme is proposed, which guarantees closed‐loop signal boundedness and asymptotic output tracking. The new adaptive compensation scheme not only expands the sensor failures types that the system could tolerate but also avoids some signal processing procedures that the traditional fault‐tolerant control techniques are forced to encounter. A complete stability analysis and a representative simulation study are conducted to evaluate the effectiveness of the proposed adaptive compensation control scheme.