Work

Adaptive neural‐based asynchronous control for nonhomogeneous Markov jumping systems with dead zones

Year: 2024

Type: article

Abstract: This article addresses the challenge of adaptive neural‐based asynchronous control for nonhomogeneous Markov jumping systems with input dead zones. Time‐varying transition probabilities are precisely characterized using a two‐layer nonhomogeneous Markov process. A hidden Markov model is employed to detect system modes and resolve the asynchronous issues of controllers. Based on the detected modes and a neural network strategy, an adaptive asynchronous control strategy is proposed. The Lyapunov stability theory is used to prove that the system remains probabilistically bounded under this control law. Finally, the effectiveness of the control strategy is demonstrated through a simulation example.

Source: IET Control Theory and Applications

DOI: 10.1049/cth2.12762

Authors: Xiang Li, Luxue Wang, Shuangsi Xue, Zihang Guo, Hui Cao

Institutions: Shaanxi University of Science and Technology, Xi'an Jiaotong University

Language: English

Topic: Stability and Control of Uncertain Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,300

OpenAlex ID: W4404156141

FWCI:

Cites: 34

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Related to: 10