• Corpus ID: 12736831

Design and Performance of PID and Fuzzy Logic Controller with Smaller Rule Set for Higher Order System

@inproceedings{VaishnavDesignAP,
  title={Design and Performance of PID and Fuzzy Logic Controller with Smaller Rule Set for Higher Order System},
  author={S. R. Vaishnav and Zafar J. Khan}
}
smaller rule set is proposed. Simulation results are demonstrated. Performance analysis shows the effectiveness of the proposed Fuzzy logic controller as compared to the ZN tuned PID controller & fine tuned PID controller. 

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References

SHOWING 1-10 OF 11 REFERENCES

Design of PID & Fuzzy Logic Controller for Higher Order System

Fuzzy gain scheduling of PID controllers

The development of a scheme for fuzzy gain scheduling of PID (proportion-integral-derivative) controllers for process control is described and results demonstrate that better control performance can be achieved in comparison with the controllers of J. Nichols and T. Kitamori's PID controllers.

The dynamic fuzzy method to tune the weight factors of neural fuzzy PID controller

The result of running shows that the neural fuzzy PID controller with PFIB has the better and satisfactory behavior for real time industrial control processing.

A developed method of tuning PID controllers with fuzzy rules for integrating processes

A fuzzy tuning scheme for PID controller settings is developed for integrator plus time delay processes in this paper, in which a fuzzy rule base reasoning method are utilized on-line to determine a tuning parameter /spl alpha/ based on the error and the first change of the error of the process.

Design of adaptive fuzzy PID tuner using optimization method

  • Jingwei XuX. Feng
  • Computer Science
    Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)
  • 2004
A novel method to design the fuzzy PID tuners which combine the PID control and fuzzy control in order to improve the system performance for complex systems in which the normal PID controller is not suitable in such a case.

PID controllers: recent tuning methods and design to specification

A brief summary of PID theory is given, then some of the most-used PID tuning methods are discussed and some the more recent promising techniques are explored.

PID control system analysis, design, and technology

It is seen that many PID variants have been developed in order to improve transient performance, but standardising and modularising PID control are desired, although challenging, and the inclusion of system identification and "intelligent" techniques in software based PID systems helps automate the entire design and tuning process to a useful degree.

PID Controllers: Theory, Design, and Tuning

Fuzzy controller : Choosing an appropriate & smallest rule set

  • International Journal of Computational Cognition
  • 2002

Fuzzy Control & Modeling:Analytical foundations and applications

  • Fuzzy Control & Modeling:Analytical foundations and applications
  • 2000