Recurrent Neural Network Controller for Linear and Nonlinear Systems

This chapter explores the application of neural networks in mechatronics for intelligent engineering applications. Mechatronics is an interdisciplinary field that involves the integration of mechanical, electrical, and computer engineering to develop advanced systems. Artificial intelligence (AI), and in particular, neural networks, have proven to be effective tools in enhancing the intelligence of mechatronic systems. The chapter provides an overview of mechatronics, AI, and neural networks, followed by a literature review discussing their applications and advantages. The results show that using neural networks in mechatronics improves the intelligence of mechatronic systems, resulting in better performance. The chapter indicates that neural networks have the potential to dramatically improve the intelligence of mechatronic systems and recommends future research directions. This study lays the groundwork for future research into the use of neural networks in mechatronics for intelligent engineering applications.

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Recurrent Neural Network Controller for Linear and Nonlinear Systems

Cited by 2 publications

References 3 publications

Recurrent neural networks with finite-time terminal sliding mode control for the fractional-order chaotic system with Gaussian noise

Recurrent neural networks with finite-time terminal sliding mode control for the fractional-order chaotic system with Gaussian noise

Applied Neural Networks in Mechatronics for Intelligent Engineering Applications

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