A fuzzy PID thermal control system for casting dies

Yang, Tiebao; Chen, Xiang; Hu, Henry; Chu, Yeou-Li; Cheng, Patrick

doi:10.1007/s10845-008-0089-1

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Because there are still unmodeled dynamics and disturbances, the Fuzzy control is used to adaptively adjust the increments Δ k p , Δ k i , and Δ k d for robustness and stability. The increments Δ k p , Δ k i , and Δ k d are online adjusted according to the output error ( e,ec ) by using many mature algorithms as presented in many publications. , …”

Section: New Intelligent Integration Control Methodsmentioning

confidence: 99%

“…The increments Δk p , Δk i , and Δk d are online adjusted according to the output error (e,ec) by using many mature algorithms as presented in many publications. 11,24 After obtaining these optimal control parameters, the proposed control method can effectively achieve the system stability, robustness, and feasibility even in the face of sudden changes and large uncertainties.…”

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

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Two-Level Modeling Based Intelligent Integration Control for Time-Varying Forging Processes

Huang

2015

Ind. Eng. Chem. Res.

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Time-varying forging processes and uncertainties and sudden changes in the deformation force or driving force pose great challenges to high-quality forging. In this paper, a two-level modeling based intelligent integration control approach is proposed to meet this challenge. It considers multiple localized nonlinear dynamics caused by the nonlinearity and the sudden changes, and also avoids the large-amplitude vibrations and even instability in the transition region. It also integrates the advantages of the tracking control and the robust control. The tracking control is to guarantee the tracking performance of the smooth operation region, while the robust control is to guarantee the robust performance of the sudden change region. To guarantee the continuity and smoothness between the smooth operation region and the sudden change region, the integration control based on both the tracking control and the robust control is developed in the transition region. Through this intelligent integration, the continuity and smoothness between the multiple localized nonlinear dynamics are guaranteed. Finally, the effectiveness of the proposed method is verified by both numerical simulations and experiments.

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Section: New Intelligent Integration Control Methodsmentioning

confidence: 99%

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

Two-Level Modeling Based Intelligent Integration Control for Time-Varying Forging Processes

Huang

2015

Ind. Eng. Chem. Res.

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“…Fig. 5 Step response and bode diagram after lag correcting PID control method is a kind of early, mature and widely used control strategy [5]. By using PID controller to adjust tension system, so as to meet constant tension.…”

Section: Adjusting the Algorithm Of Tension Controlmentioning

confidence: 99%

Design and Research on Constant Tension Controller in Electric Power Transmission

Yao

Qiu

Cao

2012

AMR

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In order to improve the characteristic and control strategy in transmission lines, a tension stringing mathematical model was established which analyzed the multiple disturbance factors of tension. According to the tension control principle of hydraulic system and the influence of different factors, a control method of constant tension adapted to the system was proposed based on pressure regulating plan. By simulation, the modified tension control system enhanced the dynamic response characteristic and stability effectively, which can realize the ideal constant tension control.

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“…Combining experience of experts with semantic inference rules, fuzzy logic system does not need complicated mathematical equations, so it is commonly used in industry (Chan et al 2003;Yang et al 2008;Önüt et al 2008). Fuzzy logic unit is composed of four main parts-fuzzifier, fuzzy rule base, fuzzy inference engine and defuzzifier.…”

Section: Fuzzy Logic Systemmentioning

confidence: 99%

Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers

2010

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By using fuzzy-base Taguchi method, this study investigates the optimal process parameters that maximize multiple performance characteristics index (MPCI) for hot extrusion of AZ31 and AZ61 magnesium alloy bicycle carriers. The larger-the-better quality characteristics of flattening strength and T-slot fracture strength as well as the smaller-the-better quality characteristic of extrusion load is considered in the MPCI. Through MPCI inference model, a manufacture method with less extrusion load and better mechanical properties under hot extrusion can be obtained. The signal-to-noise (S/N) ratios of the three quality characteristics-flattening strength, T-slot fracture strength and extrusion load-are calculated for the products based on experimental results. And the S/N ratio serves as the input variable to fuzzy control unit, and MPCI is a single output variable. The obtained MPCI is used to analyze optimal process parameters. This study finds combination of process parameters that optimizes MPCI, and conducts confirmatory experiments to prove the accuracy of optimal combination of process parameters thus selected. Finally, mechanical properties of AZ31, AZ61 magnesium alloy and A6061 aluminum alloy bicycle carriers are tested to identify differences among these three materials.

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A fuzzy PID thermal control system for casting dies

Cited by 9 publications

References 7 publications

Two-Level Modeling Based Intelligent Integration Control for Time-Varying Forging Processes

Two-Level Modeling Based Intelligent Integration Control for Time-Varying Forging Processes

Design and Research on Constant Tension Controller in Electric Power Transmission

Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers

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