2020
DOI: 10.1109/tie.2019.2898585
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Disturbance Observer Design for Nonlinear Systems Represented by Input–Output Models

Abstract: A new approach to the design of nonlinear disturbance observers for a class of nonlinear systems described by inputoutput differential equations is presented in this paper. In contrast with established forms of nonlinear disturbance observers, the most important feature of this new type of disturbance observer is that only measurement of the output variable is required, rather than the state variables. An inverse simulation model is first constructed based on knowledge of the structure and parameters of a conv… Show more

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Cited by 213 publications
(74 citation statements)
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“…Nevertheless, the determination whether nonlinear systems are observable has always been a challenging task. In [2] for example, a nonlinear disturbance observer (DOB) is presented. The DOB is used to estimate the disturbances by only utilizing the measurements of the output.…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, the determination whether nonlinear systems are observable has always been a challenging task. In [2] for example, a nonlinear disturbance observer (DOB) is presented. The DOB is used to estimate the disturbances by only utilizing the measurements of the output.…”
Section: Introductionmentioning
confidence: 99%
“…The permanent magnet synchronous motor (PMSM) is known to be a highly efficient drive for various modern electromechanical systems. Due to its multivariable control, nonlinearity and coupling, increasingly advanced control algorithms such as advanced PID control [1], [2], robust control [3], repetitive control [4], sliding mode control [5], predictive control [6], disturbance observer based control [7] and fuzzy-neural control [8] have been developed to enable easier and more effective control of the PMSM system speed.…”
Section: Introductionmentioning
confidence: 99%
“…Some methods have been well established to deal with system output constraints, such as set invariance, model predictive control, reference governors, and error transformation . In addition, adaptive control using the fuzzy logic design and neural network technique has been studied in the works of Shen et al and Ding et al Recently, the barrier Lyapunov function (BLF) has been reported in the works of Tee et al to solve the control problem of nonlinear strict‐feedback systems with output constraints. After then, BLF has been employed to design constraint control schemes for some nonlinear constraint systems with different structures, for example, input and output constrained nonlinear systems and nonlinear state‐constrained systems .…”
Section: Introductionmentioning
confidence: 99%