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controller gain中文是什么意思

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  • The linear model of the proposed system is derived to analyze the system stability and to select the controller gains
    本論文還推導出控制系統的線性化模型用來對系統進行穩定性分析和控制器參數的選擇。
  • For all admissible uncertainties and possible controller gain variations , the desgined controller can guaranteed that the closed - loop system is asymptotically stable and the upper bound of cost function value is not more than a constant
    所設計的控制器對于所允許的不確定性和控制器增益的可能變化,能保證閉環系是統漸近穩定的且性能指標上界不超過某個常數。
  • By using lmi toolbox in matlab , it is easily to obtain controllers gain matrices . 2 ) based on lyapunov stability theory , the results on robust control for time - delay systems with markovian jumping parameters are extended to neutral
    2 )基于lyapunov穩定性理論,將含有markov跳躍參數的線性不確定時滯系統的魯棒控制結果推廣到含有markov跳躍參數的中立型系統中。
  • The model - free pid control method with neuron tuning gain and the neuro - fuzzy control method for a constant cutting force metal turning process system are proposed . the former method keeps the cutting force to be constant by using the neuron to change the pid controller gain on - line . the latter method construct the fuzzy neuron controller by combing the fuzzy controller and the neuron controller
    針對具有非線性和不確定性的機械加工切削過程,提出了神經元增益自整定的pid控制方法和模糊神經元非模型控制方法,前者采用神經元來在線調整pid控制器的增益,后者將模糊控制器和神經元控制器相結合構成模糊神經元控制器,這樣當對象特性隨切削深度的變化而變化時,所設計的控制器能保持切削力恒定,使系統穩定并具有滿意的動態品質。
  • The neuron control method with self - tuning gain is proposed for a ph neutralization process . in this control system , the fuzzy t - s model is used to predict the control signal . the neuron controller gain is calculated according to the parameter estimation and experience formulas
    針對具有嚴重非線性特性的ph中和過程,提出了一種模糊增益自整定神經元控制方法,這種方法采用t - s模糊推理估計下一時刻的控制量,并通過參數估計和經驗公式來計算出神經元控制器的增益。
  • 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,給出一種神經網絡模型,提出了一種神經非模型控制方法,該方法利用模糊算法在線調整神經網絡控制器的增益,仿真實驗表明這種基于神經網絡的非模型控制方法能有效控制ph過程,具有優良的控制品質和強魯棒性。
  • To the level control problem of a spherical tank , two model - free control methods are proposed . in the former method , the takagi - sugeno fuzzy model is used to tune the neuron controller gain . in the latter method , the model - free control method using the neural network model proposed for nonlinear plants is presented
    針對具有非線性特性的球形容器液位受控對象,從增益自調整和非線性補償兩個角度,分別提出了兩種非模型控制方法,前者采用t - s模糊模型對神經元控制器的增益進行在線整定,后者使用本文建立的非線性神經元網絡對球形容器進行非模型控制。
  • On account of the uncertainty existing in the nonlinear ship responded model , we design a dynamic adaptive ship steering controller by using adaptive backstepping . after deducing the update law of the unknown constant , we choose the controller gains to guarantee the closed loop system and the control signal global boundedness
    由于船舶非線性響應模型中含有未知常參數的不確定項,因此采用自適應backstepping的方法,選擇參數自適應調節律,設計動態的船舶航向控制器,實現在線控制。
  • After getting online results , combustion expert controller gained relevant ratiocinate output results by integrating technical parameters of online inspected system , combustion computed results and diagnostic and manipulated countermeasure of knowledge base , then which could propose operator for choosing a suitable control method using concentrated corresponding rules
    在得到在線計算結果以后,燃燒專家控制器綜合在線檢測系統提供的工藝參數,以及燃燒計算的結果,使用存放在知識庫中的診斷和操作對策,得到相應的推理輸出結果;利用規則集的相應規則,提示操作工選用合適的控制方法。
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