JERAJournal of Electronic Research and Application2208-35022208-3510Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jera.v9i3.10616ArticleDesign of Mechanical Automation Control System Based on Artificial Intelligencehttps://artdesignp.com/journal/JERA/9/3/10.26689/jera.v9i3.10616SunZhen2025932025-06-05Aiming at the problems of poor adaptability and insufficient fault prediction of traditional mechanical automation control systems in complex working conditions, a mechanical automation control system based on artificial intelligence is designed. This design integrates expert control, fuzzy control, and neural network control technologies, and builds a hierarchical distributed architecture. Fault warning adopts threshold judgment and dynamic time warping pattern recognition technologies, and state monitoring realizes accurate analysis through multi-source data fusion and Kalman filtering algorithm. Practical applications show that this system can reduce the equipment failure rate by more than 30%. With the help of intelligent scheduling optimization, it can significantly improve production efficiency and reduce energy consumption, providing a reliable technical solution and practical path for the intelligent upgrade of the mechanical automation field.

Wang N, 2025, Application of Intelligent Control Technology in Mechanical Manufacturing and Automation. Journal of International Natural Science Studies, 2(1): 37–40.

Mafune Y, Katagiri N, Hanai T, et al., 2024, Material Property Control of CuSn Alloy Using Wire and Arc Additive Manufacturing (Translated): Design, Machine Element & Tribology, Information & Intelligent Technology, Manufacturing, and Systems (Selected Paper). Mechanical Engineering Journal, 11(2): 23–00568.

Min J, Wu Z, Zhang W, et al., 2023, Intelligent Liquid Crystal Elastomer Actuators with High Mechanical Strength, Self‐Sensing, and Automatic Control. Advanced Sensor Research, 3(1): 2300117.

Gondo S, Arai H, 2023, Roller Path Solver System for Multi-objective Task-priority Control of Multipass Conventional Spinning: Design, Machine Element & Tribology, Information & Intelligent Technology, Manufacturing, and Systems. Mechanical Engineering Journal, 10(5): 22–00253.

Shi XX, Zhang QY, Liu YL, 2022, Automatic Anti-interference Control of Intelligent Mechanical Communication Terminal based on Neural Network. International Journal of Information and Communication Technology, 20(1): 97–113.

Lin W, Peng L, 2021, Design of the Intelligent Manipulator Movement Control System Based on the T-S Fuzzy Model. Russian Physics Journal, 64(6): 1107–1121.

Kim M, Ra Y, Cho S, et al., 2021, Geometric Gradient Assisted Control of the Triboelectric Effect in a Smart Brake System for Self-powered Mechanical Abrasion Monitoring. Nano Energy, 89: 106448.

Mechatronics, 2019, Guest Editorial: Focused Section on Reliability Design and Resilient Control for Intelligent Mechatronic Systems (RDRC-IMS). IEEE/ASME Transactions on Mechatronics, 24(6): 2437–2440.

Deng S, Cai H, Li K, et al., 2018, The Design of Intelligent Grasping Control System for a Special Operation Manipulator. IOP Conference Series: Materials Science and Engineering, 428(1): 012005.

Han Y, 2018, Automatic Transmission and Control of Engineering Machinery Intelligent Robots for Industry 4.0. IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association, 30(6): 775–781.

Yu H, Taheri S, Duan J, et al., 2016, An Integrated Cooperative Antilock Braking Control of Regenerative and Mechanical System for a Hybrid Electric Vehicle Based on Intelligent Tire. Asian Journal of Control, 18: 55–68.

Shao BC, Zhang J, Wan Y, 2013, Study on Mechanical Automation with Intelligent Control System in Tea Crank. Applied Mechanics and Materials, 387: 267–270.

Lan CD, 2013, The Application of Intelligent Industrial Robotic Control System Based on PLC in Mechanical Automation. Advanced Materials Research, 738: 272–275.

Rasmussen J, Griepentrog H, Nielsen J, et al., 2012, Automated Intelligent Rotor Tine Cultivation and Punch Planting to Improve the Selectivity of Mechanical Intra‐row Weed Control. Weed Research, 52(4): 327–337.

Kostka P, Nawrat Z, Malota Z, 2006, Automatic Heart Valve Qualification Tester—New Mechanical Construction and Control Strategy based on Artificial Intelligence Methods. Journal of Biomechanics, 39(S1): S619.