• Corpus ID: 8072782

Boiler Flow Control Using PID and Fuzzy Logic Controller

  title={Boiler Flow Control Using PID and Fuzzy Logic Controller},
  author={Rahul Malhotra and Rajinder Sodhi},
Conventional Proportional Integral Controllers are used in many industrial applications due to their simplicity and robustness. The parameters of the various industrial processes are subjected to change due to change in the environment. These parameters may be categorized as steam, pressure, temperature of the industrial machinery in use. Various process control techniques are being developed to control these variables. In this paper, the steam flow parameters of a boiler are controlled using… 

Design of Boiler flow control using PSO technique with Optimal stabilizing controller

PID controllers are widely used in many industrial applications due to their simplicity and robustness. In this paper, control of steam flow parameters of the Boiler using conventional PID

Boiler Flow Control using Optimal Fuzzy Supervisory PID Controller

  • R. BendibN. Batout
  • Engineering
    2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)
  • 2018
The steam flow parameters of a boiler are controlled using fuzzy supervisory PID controller and then optimized using hierarchical genetic algorithm to find the best values of proportional gain (Kp), integral gain (KI), derivative gain (D).

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  • L. YaoChin-Chin Lin
  • Computer Science
    International Conference on Computational Intelligence
  • 2004
It will be shown that the proposed GS_FPID controllers learned by the accumulated GA perform well for not only the regular linear systems but also the higher order and time-delayed systems.

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Simulation results show that the proposed fuzzy PID controller produces superior control performance to the conventional PID controllers, particularly in handling nonlinearities due to time delay and saturation.

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It is clear that the proposed adaptive PID type fuzzy controller is effective in controlling such a non-linear system by changing the prediction horizon adaptively for real-time working.