Development of Control Systems and Operate Independently without Human Intervention

Hridya Venugopal*
Kings Engineering College, Chennai, Tamil Nadu, India.
Periodicity:July - December'2022
DOI : https://doi.org/10.26634/jic.10.2.19356

Abstract

The development of control systems that operate independently without human intervention is a rapidly growing field in instrumentation and control engineering. These systems are designed to function autonomously, using Artificial Intelligence (AI) and Machine Learning (ML) techniques to make decisions and perform tasks. Applications of these systems can be found in a variety of fields, including autonomous vehicles, robotics, and industrial automation. The key benefits of these systems are their ability to perform tasks without human intervention, which can lead to increased efficiency and productivity. They also have the ability to operate in environments that may be too dangerous for humans, such as deep-sea exploration or space. Additionally, they are able to collect and process large amounts of data in realtime, which can be used to improve decision-making and control. This includes the use of machine learning and evolutionary algorithms to improve the ability of systems to adapt to changing conditions. This research is also focused on the integration of these systems with communication networks, such as the internet, to enable remote monitoring and control. With advancements in technology and increasing demand for automation, it is expected that autonomous systems will play an increasingly important role in various industries in the future.

Keywords

Control Systems, Artificial Intelligence, Machine Learning Techniques, Independent Operation, Human Intervention.

How to Cite this Article?

Venugopal, H. (2022). Development of Control Systems that Operate Independently without Human Intervention. i-manager’s Journal on Instrumentation & Control Engineering, 10(2), 25-35. https://doi.org/10.26634/jic.10.2.19356

References

[11]. Joshi, A. (2017). Real-Time Implementation and Validation for Automated Path Following Lateral Control Using Hardware-in-the-Loop (HIL) Simulation (No. 2017-01-1683). SAE Technical Paper.
[15]. Otter, M., & Cellier, F. E. (2019). Software for modeling and simulating control systems. In Control System Fundamentals (pp. 419-432). CRC Press.
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