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Subject: search.filters.subject.Level process

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    New tuning formulas for two-degree of freedom PID controllers and the application to level control systems
    (2007-01-01)
    Benjanarasuth, Taworn
    ;
    Ngamwiwit, Jongkol
    ;
    Komine, Noriyuki
    ;
    Ochiai, Yasuzumi
    This paper presents novel tuning formulas for two-degree of freedom PID-family controllers. The structure of the proposed control system consists of a plant or process to be controlled, P or PI or PID controllers and a pre-filter. The tuning formulas are derived based on the CDM design method by solving CDM algebraic equations obtained from the known controllers' structures and the approximated plant model based on the experimental test. The proposed formulas are summarized in the tuning table and can be used easily. To apply the tuning rules, the plant or process is firstly tested to find the values of critical gain and critical period experimentally in the same manner as Ziegler-Nichols' second method. The parameters of P, PI or PID controller and the associated pre-filter are then obtained by substituting those values in the formulas. The experiments in controlling the level process with long pipeline controlled by the controllers tuned by the proposed rules and the well-known Ziegler-Nichols' formulas are conducted and compared. The proposed control systems result in responses with shorter settling time and considerably smaller or no overshoot. Overall, the proposed formulas are well applicable despite their simplicity.
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    Neuro-fuzzy controller design for industrial process controls
    (2004-12-01)
    Tipsuwanporn, V.
    ;
    Intajag, S.
    ;
    Witheephanich, K.
    ;
    Koetsam-ang, N.
    ;
    Samiamag, S.
    In this paper, an industrial controller is designed with the neuro-fuzzy model based on Sugeno-type fuzzy inference. The designed controller is a nonlinear system, which uses the relation between input and output data. The fuzzy system is employed as the controller, which can be tuned itself by the neural network mechanism based on a gradient descent technique. The controller is implemented with M-file and graphic user interface (GUI) of Matlab program. The program uses MPIBM3 interface card to connect with the industrial processes. The proposed controller provides the online tunable mode to adjust the fuzzy rule bases with real time. In the experimentation, the proposed method is tested by varying of the process parameters, set points and load disturbance. Two processes, which consist of the level and temperature controls, are used to evaluate the efficiency of our controller. The results of the both processes are compared with two PID systems that are 3G25A-PIDO1-E and E5AK of OMRON. From the comparison results, our controller performance can be archived in the case of more robustness than the two PID systems.