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Response curves of the variable universe and common fuzzy controls under different inputs.

Response curves of the variable universe and common fuzzy controls under different inputs.

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Selective micro heat sintering (SMHS)-type 3D printing technology is a widely applied method in rapid prototyping, which uses an electric heating component to sinter non-metallic powder. It requires precise control of the heating component's energy and its sintering time. Temperature is one of the key factors that affect the forming quality of fuse...

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... simulation result under different working conditions is shown in Fig. 5. It shows that the simulated response curves of the two different approaches were at 170 • C, 187 • C, and 238 • C. It also clearly shows that, un- der the large step jump, the universe fuzzy PID control had a better performance in terms of overshoot and time adjustment than the common fuzzy PID control; however, the former's response ...

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In gas transmission, the regulator needs to adjust the gas pressure from high to low. The pressure energy can be then recovered by an expander, and the expander can drive a generator to produce electricity. However, the gas pressure regulator system and generator torque process often present difficult adjustment of PI parameters, and strong non-linearity of the hysteresis comparator and switching table in the traditional direct torque control (DTC) cause difficulties in the controller design and lead to large fluctuations of the generator torque. This paper designs a model predictive controller (MPC) for the gas pressure regulator process to reduce generator torque fluctuations. Simultaneously, a fuzzy PI controller is designed for the generator rotational speed process, and an MPC controller is exploited for the torque process; they operate in a cascaded manner. The fuzzy PI controller is used to calculate the torque set point. And the MPC controller is designed to obtain the optimal voltage vector of the generator for improving control performance through time delay compensation. The simulation experimental results highlight that the fluctuation of the regulator outlet gas pressure is reduced by 7.9% and 8.1%, and the output torque range is reduced by 3.4% and 2.1% compared with the traditional PI control and fuzzy PI control, respectively. The generator torque fluctuation range is reduced by 82.3%, the rotational speed fluctuation range is reduced by 76.9%, and the three-phase current fluctuation range is reduced by 76.6% compared with the traditional DTC.