International Journal For Multidisciplinary Research

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Adaptive Control Systems for Industrial Automation: Enhancing Flexibility

Author(s) Saiman Shetty
Country USA
Abstract This paper explores the pivotal role of adaptive control systems in advancing industrial automation by enhancing operational flexibility. It addresses the current challenges asso- ciated with static control systems in accommodating dynamic and uncertain industrial environments. The study employs a comprehensive framework integrating real-time data analytics, machine learning algorithms, and feedback loop optimization to develop an adaptive control model. Key technologies, including neural networks and digital twin simulations, are harnessed to facilitate the system’s adaptability and scalability. The findings reveal significant improvements in operational efficiency, scalabil- ity, and responsiveness, demonstrating the potential of adaptive systems to dynamically adjust to varying process requirements and disturbances. These systems enable seamless integration of new automation technologies and rapid reconfiguration in response to changing production demands. Overall, the research underscores the strategic importance of adaptive control systems in fostering a responsive and efficient industrial automation landscape, aligning with the evolving demand for flexible and smart manufacturing solutions.
Keywords Adaptive Control Systems, Industrial Automa- tion, Flexibility in Automation, Control Theory, Real-time Con- trol, Dynamic Systems, Model-Predictive Control (MPC), Au- tomated Process Control, Industrial Robotics, Fault Tolerance, Scalability in Automation, Self-tuning Systems, Automation Ef- ficiency, Responsive Control Systems, Production Flexibility, Process Optimization, Intelligent Control
Published In Volume 1, Issue 3, November-December 2019
Published On 2019-11-22
Cite This Adaptive Control Systems for Industrial Automation: Enhancing Flexibility - Saiman Shetty - IJFMR Volume 1, Issue 3, November-December 2019. DOI 10.36948/ijfmr.2019.v01i03.2916
DOI https://doi.org/10.36948/ijfmr.2019.v01i03.2916
Short DOI https://doi.org/g8rgqn
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