approximation error造句
例句與造句
- When nonlinear degree is high , the linear approximation error must be considered
因此在非線性程度較高時(shí)，必須考慮減少線性近似誤差。 - This class , taught by the guest speaker , is devoted to the study of the approximation error , and some of its general properties
這堂課將由授課的特別來賓講解近似誤差原理及其一般特性。 - In order to improve the control performance of the closed - loop system , the adaptive compensation term of the approximation error is introduced
為改善控制系統(tǒng)的性能，引入逼近誤差的自適應(yīng)補(bǔ)償項(xiàng)。 - Simulation results of a duffing forced - oscillation system confirm that the effect of the fuzzy approximation error on the tracking error can be attenuated efficiently by the proposed method
強(qiáng)迫震?系統(tǒng)的模擬結(jié)果確定在模糊近似誤差的影響下，追蹤誤差能被有效的衰減。 - So a compensator is constructed , which is compensates the approximation error ' s effect on system output at the condition of the approximation error thought as disturbance of the system
所以利用系統(tǒng)跟蹤誤差構(gòu)造線性最優(yōu)補(bǔ)償器，該補(bǔ)償器用于減少逼近誤差對系統(tǒng)跟蹤誤差的影響。 - It's difficult to find approximation error in a sentence. 用approximation error造句挺難的
- Since the fuzzy descriptions are imprecise and may be insufficient to achieve the desired accuracy , it is necessary to design a compensator to removing the influence of the approximation error
但是由于模糊系統(tǒng)本身的缺陷，逼近誤差在一定條件下有可能較大，不能忽視，而且這種逼近誤差必然會(huì)影響系統(tǒng)的跟蹤誤差。 - The equivalence between the mamdani type fuzzy systems using trapezoid or gauss membership functions and the piecewise interpolation functions is demonstrated . and the estimation of the approximation error is given
對mamdani系統(tǒng)，分析了隸屬函數(shù)分別采用梯形和高斯型時(shí)一維模糊系統(tǒng)與函數(shù)插值的等價(jià)性和逼近誤差。 - It is shown that the proposed scheme guarantees the stability of the closed - loop system and achieves tracking performance idex , meanwhile the influences of external disturbance , neural network approximation error and the cross - coupling of input to output on the tracking error are reduced to a prescribed level
該方法不僅保證了閉環(huán)系統(tǒng)的穩(wěn)定，而且使外部干擾、神經(jīng)網(wǎng)絡(luò)逼近誤差及輸入對輸出的交叉耦合對跟蹤誤差的影響衰減到給定的水平。 - The proposed approach overcome the disadvantages which the neural network need learning off - line before using as a controller and lack of real - time and can not guarantee stability of the system , hi order to eliminate the extern disturbance and approximation error of network , the controller design combine with robust control approach and the system possess robustness
基于lyapunov穩(wěn)定性理論，推導(dǎo)出了神經(jīng)網(wǎng)絡(luò)權(quán)值在線學(xué)習(xí)規(guī)律，保證了系統(tǒng)的全局穩(wěn)定性，同時(shí)，為了消除或減小外部干擾以及神經(jīng)網(wǎng)絡(luò)逼近誤差，在控制器設(shè)計(jì)時(shí)結(jié)合了魯棒控制方法，使得系統(tǒng)具有一定的魯棒性。 - The mrafc scheme employs a reference model to provide closed - loop performance feedback for generating or modifying a fuzzy controller ' s knowledge base . the adaptive compensation term of optimal approximation error is adopted . by theoretical analysis , the closed - loop fuzzy control system is proved to be globally stable , with tracking error converging to zero
該方案利用參考模型作為閉環(huán)系統(tǒng)的反饋信號來產(chǎn)生、調(diào)節(jié)模糊控制器的規(guī)則庫，并通過引入最優(yōu)逼近誤差的自適應(yīng)補(bǔ)償項(xiàng)來消除建模誤差的影響，不但能保證閉環(huán)系統(tǒng)穩(wěn)定，而且可使跟蹤誤差收斂到零。 - Firstly , based on backstepping and the supervisory control strategy , a robust adaptive fuzzy controller is designed for a class of nonlinear systems . the first type fuzzy logic system is used to approximate the unknown part of the process . the adaptive compensation term of the optimal approximation error is adopted
本文首先針對一類不確定非線性系統(tǒng)，基于backstepping方法，利用監(jiān)督控制，引入最優(yōu)逼近誤差的自適應(yīng)補(bǔ)償項(xiàng)，并利用型模糊邏輯系統(tǒng)逼近系統(tǒng)的未知部分，提出了一種魯棒自適應(yīng)模糊控制器設(shè)計(jì)方案，運(yùn)用李亞普諾夫第二方法，先證明了閉環(huán)模糊控制系統(tǒng)全狀態(tài)有界，再證明了跟蹤誤差收斂到零。 - Secondly , based on a modified supervisory control strategy and the approximation capability of generalized multilinear fuzzy logic systems ( gmfls ) , a new scheme called model reference adaptive fuzzy control ( mrafc ) for a class of siso nonlinear systems is proposed , the external disturbances and the approximation error are considered
其次針對一類具有siso的不確定非線性系統(tǒng)，同時(shí)考慮外界干擾和建模誤差，基于一種修改的監(jiān)督控制方案并利用廣義多線性模糊邏輯系統(tǒng)的逼近能力，提出一種模型參考自適應(yīng)模糊控制器設(shè)計(jì)的新方案。 - Abstract : in this paper a new identification model constructed by neural networks with modified inputs and stable filters is presented for continuous time nonlinear systems in order to reduce the inherent network approximation errors . an adaptive law with projection algorithm is employed to adjust the parameters of networks . under certain conditions , convergence of the identification error is proved
文摘:在用神經(jīng)網(wǎng)絡(luò)進(jìn)行系統(tǒng)建模時(shí)，建模誤差的存在是難免的.為了減小這種誤差，本文對連續(xù)時(shí)間非線性系統(tǒng)提出了一種新的神經(jīng)網(wǎng)絡(luò)辨識模型，它是由帶有輸入修正的神經(jīng)網(wǎng)絡(luò)和穩(wěn)定濾波器組合而成.文中給出了權(quán)值的學(xué)習(xí)算法，即權(quán)值是根據(jù)辨識誤差的投影算法來改變，證明了在一定條件下辨識誤差的收斂性 - Because the extension of dynamic change in weak nonlinear system is not large , the robust reliable controller designed by ldi can make the whole controlled system stable when time lag and faults exit in the system , at the same time , satisfying robust performance index of the system . next , considered that the approximation error produced by ldi , the unmodeling error produced by system , the parameter uncertainties and the external disturbances can not be ignored , a dynamic neural network controller is designed to compensate their effect on line . adjusted by the state output error between the ideal model and the controlled system , the cooperation of on - line network compensator and linear h _ ( ) controller of ideal model makes the whole close - loop system guar antee robust stability and track the specified signal well
本文在基于線性微分包含( ldi )的技術(shù)基礎(chǔ)上，提出了兩種非線性系統(tǒng)的魯棒控制方法，首先討論了一類弱非線性時(shí)滯控制系統(tǒng)中的魯棒可靠控制器設(shè)計(jì)問題，由于弱非線性系統(tǒng)本身的動(dòng)態(tài)變化范圍不大，在確保整個(gè)系統(tǒng)魯棒性能指標(biāo)的前提下，當(dāng)系統(tǒng)存在時(shí)滯和故障時(shí)，通過ldi設(shè)計(jì)出的魯棒可靠控制器可以鎮(zhèn)定整個(gè)被控系統(tǒng)；其次，在考慮運(yùn)用ldi技術(shù)產(chǎn)生的逼近誤差、系統(tǒng)本身的未建模誤差及參數(shù)不確定性以及外部擾動(dòng)的影響不能被忽略的情況下，設(shè)計(jì)了在線補(bǔ)償這部分影響的動(dòng)態(tài)神經(jīng)網(wǎng)絡(luò)控制器，在理想模型和被控系統(tǒng)狀念輸出誤差的調(diào)節(jié)作用下，在線神經(jīng)網(wǎng)絡(luò)補(bǔ)償器與理想模型的線性h _控制器相互配合，使得整個(gè)閉環(huán)系統(tǒng)既可以保證魯棒穩(wěn)定性又能夠跟蹤給定的指令信號。 - Adaptive bounding technique is used to deal with unknown boundedness of approximation errors . the arbitrary output tracking accuracy is achieved by tuning the design parameters . thirdly , based on the results in chapter 3 , two design approaches of adaptive iterative learning control ( ailc ) are proposed for two classes of parametric nonlinear time - delay systems
神經(jīng)網(wǎng)絡(luò)用于逼近未知的非線性時(shí)滯函數(shù)，當(dāng)狀態(tài)不可測時(shí)，采用時(shí)滯濾波器估計(jì)系統(tǒng)狀態(tài)，利用backstepping技術(shù)設(shè)計(jì)權(quán)值自適應(yīng)律和控制律，占優(yōu)化方法處理時(shí)滯基函數(shù)，自適應(yīng)界化技術(shù)處理逼近誤差的未知上界，通過調(diào)節(jié)設(shè)計(jì)參數(shù)可以實(shí)現(xiàn)對目標(biāo)軌線任意精度的跟蹤。
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