Decoupling control of magnetically suspended motor rotor with heavy self-weight and great moment of inertia based on internal model control

2021 ◽  
pp. 107754632199761
Author(s):  
Biao Xiang ◽  
Waion Wong
Keyword(s):  
Internal Model ◽  
Degrees Of Freedom ◽  
Coupling Effect ◽  
Control Model ◽  
Internal Model Control ◽  
Moment Of Inertia ◽  
Decoupling Control ◽  
External Disturbances ◽  
Model Control ◽  
Simulation And Experiment

The control performance of magnetically suspended motor with heavy self-weight and great moment of inertia is affected by parameter uncertainty and external disturbances, and the coupling effect in radial tilting of magnetically suspended motor becomes serious with the increase of rotational speed and moment of inertia, and then, the robustness would be reduced. Therefore, an internal model control model is proposed to adjust the robustness of magnetically suspended motor. Based on the internal model control model, a decoupling internal model control model is designed for magnetically suspended motor on four degrees of freedom. Simulation and experiment are conducted to verify that the internal model control model improves the robust stability of magnetically suspended motor, and the decoupling internal model control model effectively realizes the decoupling control of magnetically suspended motor on four degrees of freedom.

The implementation of internal model control (IMC) with coordinate control model for steam power plant using HYSYS

2019 ◽  
Author(s):  
Hendrik Elvian Gayuh Prasetya ◽  
Joke Pratilastiarso ◽  
Tri Bimantara Satriyo ◽  
Erik Tridianto
Keyword(s):  
Power Plant ◽  
Internal Model ◽  
Control Model ◽  
Internal Model Control ◽  
Steam Power ◽  
Steam Power Plant ◽  
Coordinate Control ◽  
Model Control

Decoupling control of bearingless permanent magnet synchronous motors with LSSVM inverse system method and internal model controller

2020 ◽  
pp. 1-20
Author(s):  
Ke Li ◽  
Feng Ling ◽  
Xiaodong Sun ◽  
Zebin Yang
Keyword(s):  
Control System ◽  
Permanent Magnet ◽  
Internal Model ◽  
Internal Model Control ◽  
Decoupling Control ◽  
Support Vector ◽  
Inverse Models ◽  
Control Scheme ◽  
Model Control ◽  
Internal Model Controller

In this paper, a novel decoupling control scheme combining least squares support vector machines (LSSVM) inverse models and 2-degree-of-freedom (DOF) internal model controllers is employed in the decoupling control system of the bearingless permanent magnet synchronous motor (BPMSM). This scheme can be used to enhance the control properties of high-precision, fast-response, and strong-robustness for the BPMSM system, and effectively eliminate the nonlinear and coupling influence. It introduces LSSVM inverse models into the original BPMSM system to constitute a decoupled pseudo-linear system. In addition, the particle swarm optimization algorithm (PSO) is used to optimize parameters of the LSSVM, which improves its fitting ability and prediction accuracy. What is more, the internal model control scheme is used to design additional closed-loop controllers, thereby improving the robustness of the entire control system. Therefore, this scheme successfully combines the advantages of the LSSVM inverse models and the internal model controller. It can enhance the stability and the static as well as dynamic properties of the whole BPMSM system while independently adjusting the tracking and interference rejection performances. The effectiveness of the proposed scheme has been verified by simulation results at various operations.

scholarly journals Improved Internal Model Control Technique for Position Control of AC Servo Motors

2020 ◽  
Vol 19 (1) ◽  
pp. 33-40
Author(s):  
Abdul Wali Abdul Ali ◽  
Abdullah Hadi Alquhali
Keyword(s):  
Internal Model ◽  
Position Control ◽  
Internal Model Control ◽  
Control Technique ◽  
Step Response ◽  
Servo Motor ◽  
External Disturbances ◽  
Ac Servo ◽  
Model Control ◽  
Ac Servo Motor

This paper focuses on the simulation analysis of the conventional Internal Model Control (IMC) technique and the development of two proposed control techniques for the position control of AC Servo Motor. Internal Model Control (IMC) technique [1] was only able to control the AC Servo Motor under static load condition. Also, it had step response problems, and it was not robust against external disturbances. For these reasons, the IMC technique was further improved to control the AC Servo Motor under dynamic load conditions by proposing Amended Internal Model Controller (AIMC). The step response and the robustness of AIMC against external disturbances were further improved by proposing AIMC+FLC. Where a Fuzzy Logic Controller (FLC) is designed and connected with the AIMC.

Research on the Internal Model Decoupling Control of High Speed Spindle

2012 ◽  
Vol 605-607 ◽  
pp. 1496-1501
Author(s):  
Yun Song Li ◽  
Jie Meng ◽  
Ye He
Keyword(s):  
Internal Model ◽  
High Speed ◽  
Control Method ◽  
Dynamic Performance ◽  
Internal Model Control ◽  
Decoupling Control ◽  
Control Effect ◽  
Model Control ◽  
Set Up ◽  
Vector Control System

Due to the structural characteristic, the dynamic performance of the high speed spindle is influenced by multi-coupled parameters. Conventional control method can’t attain the satisfied control result. So the view of internal model decoupling control of high speed motorized spindle is put forward, which can improve the performance of vector control system. In this paper, mathematical model based on internal model control of high speed spindle is set up. And voltage and current of stator are decoupled. At last, through simulation, it is proved that the method can improve the control effect and has better robustness, dynamic characteristic. Therefore, internal model decoupling control of high speed spindle is feasible and effective.

scholarly journals Smooth Adaptive Internal Model Control Based on U Model for Nonlinear Systems with Dynamic Uncertainties

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Li Zhao ◽  
Jing Wang ◽  
Weicun Zhang
Keyword(s):  
Internal Model ◽  
Closed Loop ◽  
Control Method ◽  
Nonlinear Dynamic System ◽  
Adaptive Methods ◽  
Internal Model Control ◽  
Model Parameters ◽  
Equivalent System ◽  
External Disturbances ◽  
Model Control

An improved smooth adaptive internal model control based on U model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete U model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete U model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller.

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