Reference Tracking of Nonlinear Dynamic Systems over Additive White Gaussian Noise Channel

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Dolatkhah Takloo Somayeh; Farhadi Alireza; Khaki Sedigh Ali

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Journal Paper

Paper Information

Journal: AUT Journal of Modeling and Simulation Year:2023 | Volume:55 | Issue:2 Page(s): 359-368

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Information Journal Paper

Title

Reference Tracking of Nonlinear Dynamic Systems over Additive White Gaussian Noise Channel

Author(s)

Dolatkhah Takloo Somayeh | Farhadi Alireza | Khaki Sedigh Ali | Issue Writer Certificate

Keywords

Autonomous vehicle

tele-presence

teleoperation

AWGN channel

Monte-Carlo approximation

Abstract

This paper is concerned with state tracking as well as reference tracking of nonlinear dynamic systems with process and measurement noise over the Additive White Gaussian Noise (AWGN) channel which is subject to transmission noise and transmission power constraints. The AWGN channel is a continuous alphabet channel. Therefore, this channel is very suitable for controlling dynamic systems over wireless communication links. To address these problems, a novel encoder, decoder and controller by implementing a novel linearization method for linearizing the nonlinear dynamic systems on operating points are proposed. This method compensates for communication imperfections and maintains real-time state and reference tracking at the end of the communication link. For identifying the exact time of linearization in the encoder and decoder, the Monte-Carlo approximation is applied. Using the Monte-Carlo approximator provides a possible approximation of the estimation error in the encoder and decoder at the same time. The linearization method is based on the variable (optimal) linearization rate. A proper encoder, decoder and controller for real-time state estimation and reference tracking are proposed. The nonlinear dynamic systems which were considered in this paper have process and measurement noises. Simulation results illustrate the satisfactory state tracking and reference tracking performances of the proposed technique; while variable linearization technique is used.

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