Intelligent Adaptive Tracking Controller Design for Stochastic Switched Pure-Feedback Nonlinear Systems With Input Saturation and Non-Lower Triangular Structure

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Abstract
This paper concentrates on the design of intelligent adaptive tracking controller for stochastic switched nonlinear pure-feedback systems with input saturation and non-lower triangular structure. It needs to be emphasized that both the issues of pure-feedback structure and non-differential saturation nonlinearity are involved in the studied system. With the help of the mean-value theorem, a novel intelligent adaptive tracking controller is developed in this work to overcome the difficulty resulted from pure-feedback structure, and the inherent property of Gaussian functions is utilized to handle functions that are unknown and include all state variables. Moreover, through the universal intelligent approximation technology, a novel control strategy is constructed under the framework of backstepping, which guarantees that the tracking error can converge to a small neighborhood near the origin in the sense of mean quartic value and all signals of the nonlinear closed-loop system can be bounded in probability. Eventually, the effectiveness of the presented scheme is further illustrated by the simulation of two practical examples.
Funding Information
  • National Natural Science Foundation of China (61873151, 61773192, 61773246, 61803225, 61803238)
  • Shandong Provincial Natural Science Foundation, China (ZR2019MF009)

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