Comparison Of Traditional Thermal And Intelligent Controllers In Fusion With Neural Networks For Regulation Of Robotic Manipulator

Authors

  • Aditi Saxena, Jitendra Kumar, Vinay Kumar Deolia Author

DOI:

https://doi.org/10.48047/s6vyjp85

Keywords:

Traditional controllers, Intelligent Techniques, non-linearity, neural network controller, fuzzy logic

Abstract

Since the 1950s, scientists have faced an immense challenge in managing robotic systems. The Proportional Integral-Derivative (PID) controller was the industry standard for controlling complex structures in the early days. Nevertheless, fuzzy logic controllers emerged as a result of the inadequacy of PID controllers for nonlinear systems. Researchers continued to pursue more effective control techniques, despite the fact that these controllers offered a viable solution for nonlinear systems. One such technique that emerged as a promising solution was the neurologic controller.

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References

Acharya, D., & Das, D. K. (2021). Swarm optimization approach to design pid controller for artificially ventilated human respiratory system. Computer Methods and Programs in Biomedicine, 198, 105776.

George, Thomas, and V. Ganesan. "Advanced cuttlefish optimizer-random decision forest (ACORDF) based design of fractional order PID controller for higher-order time-delay system." Journal of Engineering, Design and Technology (2021)..

Guo, B., Zhuang, Z., Pan, J. S., & Chu, S. C. (2021). Optimal design and simulation for PID controller using fractional-order fish migration optimization algorithm. IEEE Access, 9, 8808-8819.

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Published

2025-02-03

How to Cite

Comparison Of Traditional Thermal And Intelligent Controllers In Fusion With Neural Networks For Regulation Of Robotic Manipulator (Aditi Saxena, Jitendra Kumar, Vinay Kumar Deolia , Trans.). (2025). Cuestiones De Fisioterapia, 54(3), 3198-3205. https://doi.org/10.48047/s6vyjp85