Application of Intelligent Control of Microcontroller Based on Neural Network Algorithm

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Huaimin Gong, Yongjie Peng, Dexiong Luo, Xiujun Du


This paper proposes the application of intelligent control using a neural network algorithm implemented on a microcontroller platform. Conventional control systems often face challenges in handling complex and nonlinear processes efficiently. In contrast, intelligent control systems, particularly those leveraging neural networks, offer promising solutions for addressing these challenges. By integrating neural network algorithms into microcontroller-based systems, real-time adaptability and robustness can be achieved, enhancing the control performance across various applications. This paper presents a comprehensive review of the theoretical foundations and practical implementations of intelligent control systems based on neural networks. Furthermore, it discusses the design considerations and implementation methodologies for deploying such systems on microcontroller platforms. A case study demonstrating the effectiveness of the proposed approach in enhancing control performance is also provided. Overall, this paper contributes to advancing the field of intelligent control by providing insights into its application on microcontroller platforms, thereby enabling more efficient and adaptable control solutions for diverse engineering applications.

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