網路控制器 的英文怎麼說

中文拼音 [wǎnglùkòngzhìqì]
網路控制器 英文
network controller
  • 網 : Ⅰ名詞1 （捕魚捉鳥的器具） net 2 （像網的東西） thing which looks like a net 3 （像網一樣的組織或...
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 控 : 動詞1 （告發;控告） accuse; charge 2 （控制） control; dominate 3 （使容器口兒朝下 讓裏面的液體慢...
  • 制 : Ⅰ動詞1 （製造） make; manufacture 2 （擬訂; 規定） draw up; establish 3 （用強力約束; 限定; 管束...
  • 器 : 名詞1. （器具） implement; utensil; ware 2. （器官） organ 3. （度量; 才能） capacity; talent 4. （姓氏） a surname
  • 網路 : 1. [電學] network; electric network2. （網） meshwork; system; graph （指一維復形）; mesh
  • 控制器 : controller; regulator; monitor; pilot; keyer; manipulator; control unit; control device; [自動化]...
  • 控制 : control; dominate; regulate; govern; manage; check; cybernate; manipulate; encraty; rule; rein; c...
  1. In general, there are tow nns in the system of nns - imc. one is neuro - controller, and another is neuro - emulator. the neuro - emulator emulates the model of the plant online, and gives the jacobin of the plant to neuro - controller

    它一般包括神經網路控制器和神經網路觀測器，神經網路觀測器在線辨識被控對象的模型，以此作為系統的內部模型，並且向神經網路控制器提供被控對象的梯度信息。
  2. Simulation results show that both of them have satisfactory performance and strong robustness. 2. to ph processes, which are nonlinear and time varying, the neural network model is structured and the learning algorithm is presented, based on which the model - free controller is designed, while the controller gain is scheduled by a fuzzy method

    針對具有嚴重非線性和不確定性的ph中和過程，給出一種神經網路模型，提出了一種神經非模型控制方法，該方法利用模糊演算法在線調整神經網路控制器的增益，模擬實驗表明這種基於神經網路的非模型控制方法能有效控制ph過程，具有優良的控製品質和強魯棒性。
  3. In this dissertation, two kinds of optimization, methods are proposed. firstly, only these linking weights corresponding to the control rules that affect the control performance significantly are updated in order to reduce the compute works and speed up the training progress. secondly, the updating step is adjusted adaptively in accordance with the error and the change of error of the system based on the t - s model to get better performance

    針對模糊神經網路控制器一般存在著在線權值調整計算量大、訓練時間長、過度修正權值可能導致系統劇烈振蕩等缺點，提出了兩種模糊神經網路控制器的優化方法：在線自學習過程中僅對控制性能影響大的控制規則相關的權值進行修正，以減小計算量，加快訓練速度；基於t - s模糊模型，根據偏差及偏差變化率大小動態自適應調節權值修正步長，抑制控制器輸出的劇烈變化，避免系統發生劇烈振蕩。
  4. In the control process uses two bp network. one is used as nni recognizing the model, another as neural network control device ( nnc ). but first off - line recognizes controlled device, make sure nnc initial weights

    在控制的過程中，採用兩個bp網路，一個作為神經網路辨識器（ nni ）進行辨識建模;另一個作為神經網路控制器（ nnc ） 。
  5. The dissertation described the theory of wavelet in detail and presented the method of building wavelet function, presented the learning method and adjusting factor law of bp wavelet neural - networks, designed neural - networks controller. the result of simulation showed the controller could compensate dynamic inverse error

    針對動態逆產生的逆誤差，本文對基於bp小波神經網路進行了研究，給出了學習演算法和權值調整律，設計了神經網路控制器並進行了模擬，模擬結果表明能夠較好的補償動態逆產生的誤差。
  6. The paper focus on the main steam pressure control system and introduce some ways to get the systems " mathematics model. bashed on which i present some control methods and basic theory on neural network control. i designs an neural network controller

    本文以電廠主汽壓力控制系統為研究對象，介紹了主汽壓力主要的數學模型機理建模方法及系統辨識方法，介紹了幾種控制方式以及神經網路控制基本原理，並在其基礎上設計了神經網路控制器。
  7. A robust networked controller with active disturbance rejection control is presented in this paper

    基於自抗擾控制技術設計出了具有較強魯棒性的網路控制器。
  8. Finally, stc structure is used to form a composite neural networks adaptive control system of temperature and ga is also applied to train nn controller

    最後，應用自校正控制結構組成復合神經網路自適應溫度控制系統，並對神經網路控制器進行了訓練。
  9. And the controller based on vhdl ( very high speed integration circuit hardware description language ) was designed under the fpga ( field programmable gates array ) integration environment with the values gained from the train of the neural network using matlab

    氣動柔性手指神經網路控制器是在已經對氣動柔性手指進行運動學和動力學分析的前提下，使用matlab對神經網路進行試訓，依據訓練所得的權值和閾值，在現場可編程門陣列集成環境下，基於超高速集成電路硬體描述語言完成的。
  10. This dissertation presented two new methods of robust adaptive track control for a class of mimo strong nonlinear system with external disturbance. one method makes use of taylor approximation principle to linearize the mimo strong nonlinear system at the ideal equilibrium point, meanwhile external disturbance is considered, and then designs two on - line neural network controller respectively, which can dynamically compensate the high order items of taylor series and the control signals at ideal equilibrium point under the drive of state error between linear and nonlinear system. a linear feedback controller obtained by pole assignment and two on - line neural network act on the practical mimo high nonlinear system together, guaranteeing the whole system robust stable and tracking the specified signal ; the other method designs three on - line neural networks for this class of system

    本文對於一類含有外部擾動的多輸入多輸出（ mimo ）強非線性系統，提出了兩種新的魯棒自適應跟蹤控制方法，第一種利用了taylor近似的原理，在考慮了外部擾動的情況下，將mimo強非線性系統在理想平衡點處線性化，分別設計了兩個在線神經網路控制器，在線性和非線性系統之間的狀態誤差驅動下動態補償系統的taylor近似高階項及理想平衡點處的控制信號，滿足極點配置方法的線性反饋控制器和兩個在線神經網路聯合作用於實際的被控mimo強非線性系統，在保證整個系統魯棒穩定性的情況下，能夠跟蹤給定的指令信號；另一種方法是針對這類系統設計了3個在線神經網路，分別實時抵消這類非線性系統中的非線性部分、與控制量耦合的非線性項以及外部擾動，使得受控系統的輸出可以完全跟蹤給定輸入參考信號。
  11. The added neural network can be took on as the offset to the system, so the output of the neural network is constrained as to ensure the whole robustness of the system according the requirement of robustness

    增加的神經網路控制器輸出可以看作是系統的偏差，根據系統魯棒性的要求，對神經網路的控制輸出進行限制，這樣可以確保系統的整體魯棒性。
  12. In industrial the temperature system is classed large nonlinear system. with associative memory neural network as identification and fuzzy neural network as control established model reference adaptive control system, succeeded realized single dealing control. model reference adaptive control system supplied new method for other lager nonlinear system such as flux, stress and fluid system

    溫度控制系統是典型的非線性大滯后控制系統，根據本文提出的聯想記憶神經網路辨識器，與模糊神經網路控制器相結合，建立模型參考自適應控制方案，成功的實現了對單腔電阻加熱爐的控制，模型參考自適應控制方案可以向其它大滯后非線性特性的過程式控制制參量（如流量、壓力、液位等）推廣。
  13. ( 5 ) based on fuzzy control theory, fuzzy neural network ( fnn ) controller is introduced ; the changeable area and hierarchical genetic algorithm is used to training fuzzy neural network. simulation indicated that this designed fuzzy neural controller is effective

    （ 5 ）在模糊控制的基礎上，提出了模糊神經網路控制器，並用本文提出的變區域多層遺傳演算法與bp相結合進行網路學習，在理論上證明了遺傳學習演算法的收斂性。
  14. Based on this leading control thought, this thesis introduces the project based on embedded industrial ethernet, discusses and realizes the hardware configuration and software system of the node network controller. we can build the uniform net control system using this technology

    本文給出了一個基於嵌入式工業以太網的控制方案，基於此，具體討論並實現了節點網路控制器的硬體架構和軟體體系，為工業現場最底層的設備架設了單一高效的網路結構，形成了與現有internet無縫連接的數據傳輸通道。
  15. Aiming at the control feature of large ship, the authors designed a 2 - rank derivative multi - step neural network predictive model and the algorithm of the large delay ship ' s course, and presented a fuzzy control autopilot scheme based on the model with rbf neural network and fcmac controller, it solved problems of model online identification and controller online design in traditional adaptive control, so that the high precision output follow - up control of large ship with large delay and uncertain nonlinear features can be realized

    摘要針對大型船舶控制特性，設計了船舶航向的神經網路二階導數多步預測模型及其辨識和預測演算法，提出基於徑向基函數神經網路多步預測模型和模糊小腦模型關節神經網路控制器的大時滯船舶航向模糊控制自動舵方案，解決傳統自適應控制中模型的在線辨識和控制器的在線設計問題，以達到對具有大時滯、不確定非線性特性的大型船舶實現高精度輸出跟蹤控制。
  16. So the paper combined the fuzzy logic control and recurrent neural network, and the recurrent fuzzy neural network ( rfnn ) controller is introduced into the speedsensorless vector control system. moreover, an online parameter training methodology, which is derived from the lyapunov stability theorem and gradient descent method is proposed to increase the learning capability of the rfnn. the rfnn controller has a better performance than the pi controller system ; the effectiveness of the proposed control scheme is verified by simulation results

    因此論文將模糊控制和具有優越動態性能的遞歸神經網路結合起來，取長補短，提出了一種遞歸模糊神經網路控制方法，利用神經網路來實現模糊推理，可動態的調整隸屬函數的形狀、位置以及神經網路遞歸權值，並對其與pi控制器的交流調速控制系統進行了模擬比較，模擬結果表明與普通的pi控制器相比較，遞歸模糊神經網路控制器有較好的動態性能，控制器的收斂速度快、靜差小，系統在遇到參數發生變化和外部不確定性問題時魯棒性、抗擾動性有明顯的提高。
  17. In the last chapter, i presented the ways to design a neural control network and its arithmetic and gained a better control result than classical control method. liu ru _ tie ( thermal power engineering for power plants ) directed by prof. ma ping and senior engineer li jian _ min

    在本文的最後一章里，介紹了神經網路控制器的設計方法和演算法，經模擬發現，神經網路控制器比常規pid控制取得了更好的控制效果。
  18. Second, the paper introduces the modeling of the major variable pitch wind turbine generator in detail and presents the simulink result of the major variable pitch wind turbine generator without controller. third, in the third chapter the paper puts forward a control tactics of the major variable pitch wind turbine generator. for comparing conveniently with the neural networks controller and the fuzzy controller that have been designed in the later chapters, this paper gives the simulink result of the major variable pitch wind turbine generator with pid controller in brief

    首先，簡單地介紹了控制理論、神經網路和模糊控制的發展概況以及風力發電機的現狀；其次，詳細地介紹了大型變槳距風力發電機的模型的建立，並給出了風力發電機系統的開環模擬結果；接著，在第三章提出了大型變槳距風力發電機的控制策略，為了便於和後面設計出的神經網路控制器和模糊控制器相比較，本論文還簡要地作出了pid控制器的模擬結果；然後，分別設計出了神經網路控制器和模糊控制器並模擬出了令人滿意的結果。
  19. We discuss the new highway model and intelligent control method. we model the urban highway traffic flow and design a multi - variables control strategy with both the on - ramp control and the road speed control by the ann technique. the developed adaptive neural controller is to control the traffic density and force it to follow a desired one

    利甩人工神經網路技術建立了城市間高速公路的神經網路模型?並提出了入只匝道放行和路段速度控制相結合的多變量神經網路控制策略，利用診珍制策略建立的自適應神經網路控制器，可以使高速公路上的密度維持在理想值附近。
  20. Finally, the paper studies some advanced strategies. genetic algorithms ( ga ) is used to optimize the pid parameters. neural networks ( nn ) and model reference adaptive control ( mrac ) controllers are put forth to improve the performance of the simulator

    並基於轉臺模型設計了神經網路控制器和模型參考自適應控制系統，通過模擬結果證明了這兩種方法的優越性和可實現性。
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