Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System
碩士 === 國立臺北科技大學 === 機電整合研究所 === 94 === In this thesis, a novel control architecture, Grey-CMAPIC, which is based on the Cerebellar Model Articulation PI Controller (CMAPIC) and the intensity grey decision prediction controller (IGDPC), is proposed. Also, the Grey-CMAPIC is employed to improve the pe...
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ndltd-TW-094TIT056510312019-06-27T05:09:04Z http://ndltd.ncl.edu.tw/handle/9f7387 Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System 適應性向量控制系統之灰色小腦模型控制器設計 Ming-Jay Tsai 蔡明傑 碩士 國立臺北科技大學 機電整合研究所 94 In this thesis, a novel control architecture, Grey-CMAPIC, which is based on the Cerebellar Model Articulation PI Controller (CMAPIC) and the intensity grey decision prediction controller (IGDPC), is proposed. Also, the Grey-CMAPIC is employed to improve the performance of vector control system of induction motor. In general, the merits of the CMAPIC include rapid learning convergence, simple structure, on-line training, and non-linear learning ability. However, in order to enhance the performance of conventional CMAPIC, this thesis proposes the Grey-CMAPIC which is integrated with the CMAPIC and the grey-prediction compensator. The proposed Grey-CMAPIC experimentally not only improves the transient response but also yields better steady-state performance, especially on the load disturbance tolerance, parameter variation tolerance, and accuracy. The structure of the vector control system in the thesis adopts the Direct Rotor Flux Orientation Control (DRFOC), and thus the design of flux and speed estimator is one of the main focuses. The adaptive control method is used to design the pseudo-reduced-order flux observer. Moreover, for implementing the sensor-less vector control, this study uses the CMAC to estimate speed and rotor resistance, and consequently the problem of inaccurate flux estimation due to rotor resistance variation is solved. According to the experimental results, under the speed command from 2% to 100% of rated speed, the load of 8Nm, and the operation range between 36rpm to 2000 rpm, it is seen that the dynamic behavior of induction motor vector control system equipped with the novel Grey-CMAPIC performs well as comparing to the conventional CMAPIC, and the robustness remains in the presence of parameter variations 王順源 2006 學位論文 ; thesis 102 zh-TW |
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碩士 === 國立臺北科技大學 === 機電整合研究所 === 94 === In this thesis, a novel control architecture, Grey-CMAPIC, which is based on the Cerebellar Model Articulation PI Controller (CMAPIC) and the intensity grey decision prediction controller (IGDPC), is proposed. Also, the Grey-CMAPIC is employed to improve the performance of vector control system of induction motor.
In general, the merits of the CMAPIC include rapid learning convergence, simple structure, on-line training, and non-linear learning ability. However, in order to enhance the performance of conventional CMAPIC, this thesis proposes the Grey-CMAPIC which is integrated with the CMAPIC and the grey-prediction compensator. The proposed Grey-CMAPIC experimentally not only improves the transient response but also yields better steady-state performance, especially on the load disturbance tolerance, parameter variation tolerance, and accuracy.
The structure of the vector control system in the thesis adopts the Direct Rotor Flux Orientation Control (DRFOC), and thus the design of flux and speed estimator is one of the main focuses. The adaptive control method is used to design the pseudo-reduced-order flux observer. Moreover, for implementing the sensor-less vector control, this study uses the CMAC to estimate speed and rotor resistance, and consequently the problem of inaccurate flux estimation due to rotor resistance variation is solved.
According to the experimental results, under the speed command from 2% to 100% of rated speed, the load of 8Nm, and the operation range between 36rpm to 2000 rpm, it is seen that the dynamic behavior of induction motor vector control system equipped with the novel Grey-CMAPIC performs well as comparing to the conventional CMAPIC, and the robustness remains in the presence of parameter variations
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王順源 |
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王順源 Ming-Jay Tsai 蔡明傑 |
author |
Ming-Jay Tsai 蔡明傑 |
spellingShingle |
Ming-Jay Tsai 蔡明傑 Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
author_sort |
Ming-Jay Tsai |
title |
Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
title_short |
Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
title_full |
Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
title_fullStr |
Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
title_full_unstemmed |
Design of Grey-Cerebellar Model Articulation Controllers for Adaptive Vector Control System |
title_sort |
design of grey-cerebellar model articulation controllers for adaptive vector control system |
publishDate |
2006 |
url |
http://ndltd.ncl.edu.tw/handle/9f7387 |
work_keys_str_mv |
AT mingjaytsai designofgreycerebellarmodelarticulationcontrollersforadaptivevectorcontrolsystem AT càimíngjié designofgreycerebellarmodelarticulationcontrollersforadaptivevectorcontrolsystem AT mingjaytsai shìyīngxìngxiàngliàngkòngzhìxìtǒngzhīhuīsèxiǎonǎomóxíngkòngzhìqìshèjì AT càimíngjié shìyīngxìngxiàngliàngkòngzhìxìtǒngzhīhuīsèxiǎonǎomóxíngkòngzhìqìshèjì |
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