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self-tuning control in Chinese

Pronunciation:
How to pronounce "self-tuning control""self-tuning control" in a sentence

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  • 自校正控制

Examples

  • A self - tuning control for the aeroengine is proposed
    提出了航空發(fā)動機的自校正控制方案。
  • Self - tuning control
    自校正控制
  • Simulation of speed - adjustment system on neural network self - tuning control for brushless dc motor
    基于神經(jīng)網(wǎng)絡的無刷直流電機調(diào)速系統(tǒng)的仿真
  • It provides an effective way to realize self - tuning control in air - conditioning systems
    該辨識算法為空調(diào)對象的自適應控制提供了重要的手段。
  • The parameters estimation with the least square method is applied to the open speed system . the least square estimation with forgetting factor and the least square error self - tuning control are applied to the close speed system and controller parameters arc obtained from estimation parameters directly
    采用最小二乘參數(shù)估計算法對某渦扇發(fā)動機低壓轉(zhuǎn)速進行開環(huán)辨識，采用帶遺忘因子的最小二乘估和直接獲得控制器參數(shù)的自校正控制對該系統(tǒng)進行閉環(huán)控制。
  • Based on compensation control thought , through using neural network pid controller as compensation tache of traditional pid controller , a kind of hybrid pid controller is designed . combined with neural network , self - tuning control can realized better control over non - linear system . utilizing the advantages of fuzzy control and neural network control , a kind of neural network adaptive fuzzy controller based on fast bp algorithm is presented and it may control the plant on line . at last , the hybrid pid controller is applied in tension system of h - section continuous rolling mills and tension - free control is realized . the simulation results show that it has better performance than traditional pid controller . at the same time , it provides some reference for the control of other similar systems
    在此基礎上，基于補償控制思想，利用神經(jīng)pid對傳統(tǒng)pid進行補償，設計了一種混合pid控制器；神經(jīng)網(wǎng)絡與自校正控制的結合，使得自校正方法能對非線性系統(tǒng)實現(xiàn)比較理想的控制效果；利用模糊控制與神經(jīng)網(wǎng)絡控制各自的優(yōu)點，提出了一種基于快速bp算法的神經(jīng)網(wǎng)絡自適應模糊控制器，能夠?qū)ο到y(tǒng)進行在線控制。最后將混合pid控制應用于h型鋼連軋機張力系統(tǒng)中，實現(xiàn)微張力控制，仿真結果說明其較傳統(tǒng)pid具有更好的性能，同時也為其它類似系統(tǒng)的控制提供一些參考。
  • ( 6 ) this dissertation makes a detailed study of the nn based adaptive control of nonlinear dynamic systems . two types of drnn controllers are designed using the experimental samples , which are named the open - loop controller and the close - loop controller respectively . the experimental mechanism is controlled on - line by means of the nn based direct self - tuning control strategy and the nn based indirect adaptive control strategy
    6 .本文對基于神經(jīng)網(wǎng)絡的非線性動態(tài)系統(tǒng)自適應控制方法進行了深入研究,利用實驗輸入輸出數(shù)據(jù)離線設計了動態(tài)遞歸神經(jīng)網(wǎng)絡開環(huán)、閉環(huán)控制器,并分別采用基于神經(jīng)網(wǎng)絡的直接自校正控制方法與基于神經(jīng)網(wǎng)絡的間接自適應控制方法對彈性連桿機構實施了在線控制。
  • The feasibility and requirement of adaptive control applied to the control system are analysized . the model of the hydraulic servo system is created , simplified and dispersed . according to the characteristics and problems that exist in the control system of stretch - bending machine at present , the self - tuning control with pole placement is firstly introduced , which establishes the theoretical foundation for the development and research of the intelligent control system of the stretch - bending machine
    分析了拉彎機控制系統(tǒng)采用自適應控制的必要和性可行性；建立了液壓伺服控制系統(tǒng)的數(shù)學模型，并進行了簡化和離散化；根據(jù)目前拉彎機控制系統(tǒng)的特點和存在的問題，第一次把極點配置自校正控制算法引入拉彎機控制系統(tǒng)中，為智能化拉彎機控制系統(tǒng)的研究和開發(fā)奠定了理論基礎。
  • 5 . applying the theory of adaptive control to electro - hydraulic position servo system , bring forward a adaptive control method based on regulating gain and damp , a adaptive control method of approach track based on parameter identification , a self - tuning control method of pole placement , a adaptive control method of general predictive
    將自適應控制理論應用于電液位置伺服系統(tǒng)，提出了基于增益和阻尼比調(diào)節(jié)的自適應控制、基于參數(shù)辨識的漸近跟蹤自適應控制、極點配置的自校正控制和廣義預測的自適應控制。
  • Then , as the substitute of the traditional pi controller , neuron adaptive psd controller is used to alternate the velocity loop of dc driver system , , simulation results show that the super - shoot in new system is small and the performance in the way of anti - disturbance and anti - time - varying parameters are higher than the traditional pi controller and robustness of the dc driver system improved greatly , , in addition , through analysis of the character of the neuron adaptive psd controller , the paper presents a neural network self - tuning control method for dc driver system in which the diagonal recurrent neural network is used to identify the plant to calculate the plant ' s sensitivity for psd controllers simulation results indicate that excellent static dynamic target was got with this control method and the performance of the system is improved greatly ,
    然后，應用單神經(jīng)元自適應psd控制器改造調(diào)速系統(tǒng)的轉(zhuǎn)速環(huán)，代替?zhèn)鹘y(tǒng)pi調(diào)節(jié)方式的轉(zhuǎn)速控制器。仿真表明，新系統(tǒng)在超調(diào)、抗負載擾動和參數(shù)時變方面性能優(yōu)于的傳統(tǒng)的pi控制方式，系統(tǒng)的魯棒性增強。在分析單神經(jīng)元自適應psd控制器特性后，本文提出用對角遞歸神經(jīng)網(wǎng)絡辯識控制對象，為psd控制器提供靈敏度參數(shù)，從而構成一神經(jīng)網(wǎng)絡自校正控制方案。
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