Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems
碩士 === 國立臺北科技大學 === 電能轉換與控制產業碩士專班 === 103 === In this thesis, an adaptive recurrent wavelet cerebellar model articulation controller (ARWCMAC) that integrates a diagonal recurrent neural network and a cerebellar model articulation controller (CMAC) as well as wavelet functions is proposed. The ARWCM...
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ndltd-TW-103TIT057750012019-07-14T03:34:05Z http://ndltd.ncl.edu.tw/handle/4pxc5w Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems 感應馬達直接轉矩控制驅動系統之適應性遞迴小波小腦模型控制器設計 An-Hsiu Su 蘇安修 碩士 國立臺北科技大學 電能轉換與控制產業碩士專班 103 In this thesis, an adaptive recurrent wavelet cerebellar model articulation controller (ARWCMAC) that integrates a diagonal recurrent neural network and a cerebellar model articulation controller (CMAC) as well as wavelet functions is proposed. The ARWCMAC was then applied as a speed controller in an induction motor by using the direct torque control scheme. Because the traditional CMAC taking only two states for mapping the input to association memory, the output is discontinuous and result in the disadvantage of non-differentiation. To improve the shortcoming mentioned above, the continuous wavelet functions were used in the diagonal recurrent cerebellar model articulation controller (DRWCMAC) architecture for mapping the input to association memory. The input layer can take an arbitrary real value between 0 and 1, which increases adaptive capability and smoothens the control amount output of the controller. According to the feedback property of the DRWCMAC, the characteristics of dynamic behavior and data storage were inherited. This dynamic and continuous mapping property can therefore improve the drawbacks of traditional CMAC. Moreover, to ensure system stability, the adaptive rules of the RWCMAC were determined using an analytical method based on a Lyapunov stability theorem, and the gradient descent was used to update the adaptive rules of the recurrent weights. Finally, for the realization of the proposed system, the ARWCMAC, fuzzy flux controller, fuzzy torque controller, and speed estimator were integrated and implemented in a direct torque control induction motor drive system to realize the proposed system. The simulation results showed that the proposed controller achieves superior speed control compared with controllers developed through other methods. After verifying the feasibility of the proposed controller through simulation, the hardware was implemented, and several experimental tests were conducted by induction motors. Experimental results at 8 Nm load torque in a speed range form 36 rpm to 2000 rpm and ±1200 rpm showed that the proposed controller has a superior speed response than traditional CMAC. Shun-Yuan Wang 王順源 學位論文 ; thesis 0 zh-TW |
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碩士 === 國立臺北科技大學 === 電能轉換與控制產業碩士專班 === 103 === In this thesis, an adaptive recurrent wavelet cerebellar model articulation controller (ARWCMAC) that integrates a diagonal recurrent neural network and a cerebellar model articulation controller (CMAC) as well as wavelet functions is proposed. The ARWCMAC was then applied as a speed controller in an induction motor by using the direct torque control scheme.
Because the traditional CMAC taking only two states for mapping the input to association memory, the output is discontinuous and result in the disadvantage of non-differentiation. To improve the shortcoming mentioned above, the continuous wavelet functions were used in the diagonal recurrent cerebellar model articulation controller (DRWCMAC) architecture for mapping the input to association memory. The input layer can take an arbitrary real value between 0 and 1, which increases adaptive capability and smoothens the control amount output of the controller. According to the feedback property of the DRWCMAC, the characteristics of dynamic behavior and data storage were inherited. This dynamic and continuous mapping property can therefore improve the drawbacks of traditional CMAC. Moreover, to ensure system stability, the adaptive rules of the RWCMAC were determined using an analytical method based on a Lyapunov stability theorem, and the gradient descent was used to update the adaptive rules of the recurrent weights.
Finally, for the realization of the proposed system, the ARWCMAC, fuzzy flux controller, fuzzy torque controller, and speed estimator were integrated and implemented in a direct torque control induction motor drive system to realize the proposed system. The simulation results showed that the proposed controller achieves superior speed control compared with controllers developed through other methods. After verifying the feasibility of the proposed controller through simulation, the hardware was implemented, and several experimental tests were conducted by induction motors. Experimental results at 8 Nm load torque in a speed range form 36 rpm to 2000 rpm and ±1200 rpm showed that the proposed controller has a superior speed response than traditional CMAC.
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author2 |
Shun-Yuan Wang |
author_facet |
Shun-Yuan Wang An-Hsiu Su 蘇安修 |
author |
An-Hsiu Su 蘇安修 |
spellingShingle |
An-Hsiu Su 蘇安修 Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
author_sort |
An-Hsiu Su |
title |
Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
title_short |
Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
title_full |
Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
title_fullStr |
Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
title_full_unstemmed |
Design of Adaptive Recurrent Wavelet Cerebellar Model Articulation Controller for Induction Motor Direct Torque Control Drive Systems |
title_sort |
design of adaptive recurrent wavelet cerebellar model articulation controller for induction motor direct torque control drive systems |
url |
http://ndltd.ncl.edu.tw/handle/4pxc5w |
work_keys_str_mv |
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