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基于自適應灰色預測和干擾觀測器的伺服干擾抑制方法
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國家自然科學基金項目(51175267、51475243)


Method of Servo Interference Suppression Based on Adaptive Grey Predictive Controller and Disturbance Observer
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    摘要:

    為提高穩(wěn)定平臺伺服系統(tǒng)的響應和抗干擾能力,提出了一種基于自適應灰色預測(AGPC)——分數(shù)階改進干擾觀測器(FIDOB)的穩(wěn)定平臺伺服干擾抑制方法。GM(1,1)冪模型對系統(tǒng)輸出進行建模并設計了自調(diào)節(jié)模塊,將預測誤差和實際誤差加權合成一個綜合誤差,分別根據(jù)實際誤差和預測誤差的大小同時調(diào)節(jié)預測步長和預測誤差的權值,提高系統(tǒng)的響應性,減小預測誤差對系統(tǒng)的輸出影響;構造了分數(shù)階改進干擾觀測器,并詳細推導了分數(shù)階改進干擾觀測器的魯棒穩(wěn)定性。最后通過數(shù)值仿真實驗表明,該方法不僅可以有效抑制穩(wěn)定平臺外界干擾和測量噪聲,而且提高了系統(tǒng)響應能力。仿真實驗中,在摩擦和測量噪聲干擾情況下,穩(wěn)定平臺系統(tǒng)速度環(huán)的跟蹤誤差可以達到不超過0.1rad/s。在靜態(tài)和動態(tài)實驗中,穩(wěn)定平臺的調(diào)節(jié)時間縮短了0.258s,穩(wěn)定精度提高了約1.5°~2.5°。

    Abstract:

    In order to improve the response and vibration suppression abilities of stabilized platform servo system, a novel vibration suppression strategy was proposed by using an integration of fractional-order improved disturbance observer (FIDOB) based on adaptive grey predictive controller (AGPC) in stabilized platform system. A method of system modeling output module was established based on GM(1,1) power module and an adaptive adjust module was designed. The predicted error and actual error were combined together to form an integrate error, according to the values of the actual control system error and the predicted error, the prediction step and predicted error weight were adjusted to improve the response ability of system and decrease the influence of predicted error on the system output. The fractional-order improved DOB was established, and the robust stability was derived in detail. FIDOB was used to obtain disturbance estimate and generate compensation signal, and as the order of Q-filter was expanded to realnumber domain, FIDOB had a wide range to select a suitable tradeoff between robustness and vibration suppression. Finally, numerical simulation results illustrated that the method can suppress external disturbances and measurement noise well, and it can also improve the response ability of system. The proposed control strategy was simple in control-law derivation, and its effectiveness was validated by numerical simulations. In numerical simulation experiments, with the interference of friction and measurement noise, the tracking error of stabilized platform system was no more than 0.1rad/s. In the static and dynamic experiments, the regulating time of the stabilized platform was decreased by 0.258s, and the stable precision was increased by 1.5°~2.5°.

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孟紅波,王昌明,張愛軍,包建東,何博俠.基于自適應灰色預測和干擾觀測器的伺服干擾抑制方法[J].農(nóng)業(yè)機械學報,2016,47(4):333-342. Meng Hongbo, Wang Changming, Zhang Aijun, Bao Jiandong, He Boxia. Method of Servo Interference Suppression Based on Adaptive Grey Predictive Controller and Disturbance Observer[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(4):333-342.

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  • 收稿日期:2015-12-11
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  • 在線發(fā)布日期: 2016-04-10
  • 出版日期: 2016-04-10