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An Observer Based Sampled-data Control for Class of Scalar Nonlinear Systems Using Continualized Discretization Method

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  • Control Theory and Applications
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Abstract

A new observer based sampled-data feedback control is proposed for a class of scalar nonlinear affine systems, where the control distribution is constant, in the presence of noise. The discrete-time states are estimated by a nonlinear state observer, and used for designing the sampled-data control. The discrete-time model used for controller and state observer design is derived using continualizated discretization method. This discretization method is based on the new concept of continualization of discrete-time models, and is applicable to any system whose Jacobian matrix is defined. In this work, it is shown that for the system without the presence of noise, the proposed sampled-data control preserves the equilibria and dynamics of the desired system, while the conventional control, which is based on forward difference method, does not. Simulations are carried out for the scalar Riccati system with the presence of noise to demonstrate the better performances of the proposed method not only in sampled-data control design, but also in system states estimation than the conventional method for both high and low sampling frequencies.

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Correspondence to Triet Nguyen-Van.

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Recommended by Associate Editor Ohmin Kwon under the direction of Editor Fuchun Sun.

Triet Nguyen-Van received his B.S., M.S., and Ph.D. degrees in control system from the University of Tsukuba, Japan, in 2010, 2012, and 2015, respectively. He is currently a project assistant professor at the University of Tokyo. His research interests include sampled-data control, nonlinear control, power control, and smart-grid.

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Nguyen-Van, T. An Observer Based Sampled-data Control for Class of Scalar Nonlinear Systems Using Continualized Discretization Method. Int. J. Control Autom. Syst. 16, 709–716 (2018). https://doi.org/10.1007/s12555-016-0739-6

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  • DOI: https://doi.org/10.1007/s12555-016-0739-6

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