A multiple-model based internal model control method for power control of small pressurized water reactors

Energy ◽  
2020 ◽  
Vol 210 ◽  
pp. 118527 ◽  
Author(s):  
Pengfei Wang ◽  
Zhi Chen ◽  
Longtao Liao ◽  
Jiashuang Wan ◽  
Shifa Wu
Keyword(s):  
Power Control ◽  
Internal Model ◽  
Control Method ◽  
Internal Model Control ◽  
Pressurized Water Reactors ◽  
Multiple Model ◽  
Pressurized Water ◽  
Model Based ◽  
Model Control ◽  
Water Reactors

Stable control of the high-speeding magnetically suspended rotor based on extended state observer and two-degree freedom internal model control for control moment gyros with serious moving-gimbal effects

2020 ◽  
Vol 42 (14) ◽  
pp. 2733-2743
Author(s):  
Jiqiang Tang ◽  
Tongkun Wei ◽  
Qichao Lv ◽  
Xu Cui
Keyword(s):  
Internal Model ◽  
Feedback Linearization ◽  
Control Method ◽  
Fast Response ◽  
State Observer ◽  
Internal Model Control ◽  
Extended State Observer ◽  
Extended State ◽  
Control Moment ◽  
Model Control

For a magnetically suspended control moment gyro (MSCMG), which is an ideal attitude actuator for its large outputting control moment and fast response, the moving-gimbal effects due to the coupling between the moving gimbal and high-speeding rotor will make the magnetically suspended rotor (MSR) unstable. To improve control precision, both the dynamic model of MSR and the feedback linearization control are done to decouple tilting motion, and poles of the system are reconfigured to reduce control error. To suppress the varying disturbance moments caused by moving-gimbal effects, an extended state observer (ESO) is originally designed to estimate and compensate them timely and accurately. To improve system robustness, a two-degree freedom internal model control (2-DOF IMC) is researched to suppress model error. Compared with existing proportional integral derivative (PID) control method, simulations done on a single gimbal MSCMG with 200 N.m.s angular momentum indicated that this presented control method with ESO and 2-DOF IMC can suppress the moving-gimbal effects more effectively and make the rotor suspension more stable.

Model-Based Gain Scheduling Strategy for an Internal Model Control-Based Boost Pressure Controller in Variable Geometric Turbocharger System of Diesel Engines

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Seungwoo Hong ◽  
Inseok Park ◽  
Myoungho Sunwoo
Keyword(s):  
Diesel Engines ◽  
Internal Model ◽  
Gain Scheduling ◽  
Internal Model Control ◽  
Operating Conditions ◽  
Boost Pressure ◽  
Scheduling Strategy ◽  
Model Based ◽  
Model Control ◽  
Pressure Controller

This paper proposes a model-based gain scheduling strategy of a Skogestad internal model control (SIMC)-based boost pressure controller for passenger car diesel engines. This gain scheduling strategy is proposed with a new scheduling variable to handle the nonlinear variable geometric turbocharger (VGT) plant characteristics. The scheduling variable is derived from the pressure ratio between the exhaust and intake manifolds and the exhaust air-to-fuel ratio to estimate the static gain of the VGT plant, which varies widely with change in the engine operating conditions. The proposed static gain model was designed with the scheduling variable, engine speed, and fuel injection quantity. Compared to the steady-state experimental data, the static gain model showed an R-squared value of 0.91. The boost pressure controller had the proportional-integral (PI) structure to allow for online calibration, and the PI gains were determined using the SIMC method. The proposed static gain model for the VGT plant was integrated into the SIMC control structure to obtain the appropriate control gains under wide engine operating area. The proposed control algorithm was compared with a fixed gain boost pressure controller through various step tests of the desired boost pressure. The fixed gain controller showed a large overshoot of 64% when the exhaust gas recirculation (EGR) operating condition was changed. In contrast, the proposed gain scheduled boost pressure controller reduced the overshoot to 12%. The model-based gain scheduling strategy successfully adjusted the control gains to achieve consistent control performance under various engine operating conditions.

scholarly journals Current Control Methods for an Asymmetric Six-Phase Permanent Magnet Synchronous Motor

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 172 ◽  
Author(s):  
Zhihong Wu ◽  
Weisong Gu ◽  
Yuan Zhu ◽  
Ke Lu
Keyword(s):  
Permanent Magnet ◽  
Internal Model ◽  
Control Method ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
Current Control ◽  
Internal Model Control ◽  
Lms Algorithm ◽  
Least Mean Square ◽  
Model Control

Via the vector space decomposition (VSD) transformation, the currents in an asymmetric six-phase permanent magnet synchronous motor (ASP_PMSM) can be decoupled into three orthogonal subspaces. Control of α–β currents in α–β subspace is important for torque regulation, while control of x-y currents in x-y subspace can suppress the harmonics due to the dead time of converters and other nonlinear factors. The zero-sequence components in O1-O2 subspace are 0 due to isolated neutral points. In α–β subspace, a state observer is constructed by introducing the error variable between the real current and the internal model current based on the internal model control method, which can improve the current control performance compared to the traditional internal model control method. In x–y subspace, in order to suppress the current harmonics, an adaptive-linear-neuron (ADALINE)-based control algorithm is employed to generate the compensation voltage, which is self-tuned by minimizing the estimated current distortion through the least mean square (LMS) algorithm. The modulation technique to implement the four-dimensional current control based on the three-phase SVPWM is given. The experimental results validate the robustness and effectiveness of the proposed control method.

scholarly journals New Smith Internal Model Control of Two-Motor Drive System Based on Neural Network Generalized Inverse

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Guohai Liu ◽  
Jun Yuan ◽  
Wenxiang Zhao ◽  
Yaojie Mi
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Internal Model ◽  
Generalized Inverse ◽  
Control Structure ◽  
Control Method ◽  
Internal Model Control ◽  
Drive System ◽  
Motor Drive ◽  
Model Control

Multimotor drive system is widely applied in industrial control system. Considering the characteristics of multi-input multioutput, nonlinear, strong-coupling, and time-varying delay in two-motor drive systems, this paper proposes a new Smith internal model (SIM) control method, which is based on neural network generalized inverse (NNGI). This control strategy adopts the NNGI system to settle the decoupling issue and utilizes the SIM control structure to solve the delay problem. The NNGI method can decouple the original system into several composite pseudolinear subsystems and also complete the pole-zero allocation of subsystems. Furthermore, based on the precise model of pseudolinear system, the proposed SIM control structure is used to compensate the network delay and enhance the interference resisting the ability of the whole system. Both simulation and experimental results are given, verifying that the proposed control strategy can effectively solve the decoupling problem and exhibits the strong robustness to load impact disturbance at various operations.

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