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Design of a new type of neural network sliding-mode controller

Wei Wang

Open publisher page 2 citations

Abstract

As for the chattering in the sliding mode control,a new sliding mode control method based on neural network is proposed in this paper. A neural network is used to simulate the function between the state hyperplane of the system and the reaching law.A hyperbolic tangent function is applied to replace the saturation function to realize the boundary method design of the sliding mode control.Simulation results show that the neural network sliding mode control eliminates the chattering effectively.

About this research paper

What this paper is about

As for the chattering in the sliding mode control,a new sliding mode control method based on neural network is proposed in this paper. A neural network is used to simulate the function between the state hyperplane of the system and the reaching law.A hyperbolic tangent function is applied to replace the saturation function to realize the boundary method design of the sliding mode control.Simulation results show that the neural network sliding mode control eliminates the chattering effectively.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

As for the chattering in the sliding mode control,a new sliding mode control method based on neural network is proposed in this paper. A neural network is used to simulate the function between the state hyperplane of the system and the reaching law.A hyperbolic tangent function is applied to replace the saturation function to realize the boundary method design of the sliding mode control.Simulation results show that the neural network sliding mode control eliminates the chattering effectively.

Key concepts: Sliding mode control, Control theory (sociology), Artificial neural network, Variable structure control, Hyperplane, Hyperbolic function, State observer, Mode (computer interface)

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