tuning control造句
例句與造句
- A self - tuning control for the aeroengine is proposed
提出了航空發(fā)動(dòng)機(jī)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(luò)的無刷直流電機(jī)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(shí)算法為空調(diào)對(duì)象的自適應(yīng)控制提供了重要的手段。 - The advantage spark has is fine - tuned control of the operations at each step along the way , along with the capability of inserting custom code into the process
Spark的優(yōu)點(diǎn)在于，它對(duì)整個(gè)過程中每一步操作的控制都進(jìn)行了微調(diào)，還提供了將定制代碼插入到過程中的能力。 - It's difficult to find tuning control in a sentence. 用tuning control造句挺難的
- 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(jì)算法對(duì)某渦扇發(fā)動(dòng)機(jī)低壓轉(zhuǎn)速進(jìn)行開環(huán)辨識(shí)，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(duì)該系統(tǒng)進(jìn)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(chǔ)上，基于補(bǔ)償控制思想，利用神經(jīng)pid對(duì)傳統(tǒng)pid進(jìn)行補(bǔ)償，設(shè)計(jì)了一種混合pid控制器；神經(jīng)網(wǎng)絡(luò)與自校正控制的結(jié)合，使得自校正方法能對(duì)非線性系統(tǒng)實(shí)現(xiàn)比較理想的控制效果；利用模糊控制與神經(jīng)網(wǎng)絡(luò)控制各自的優(yōu)點(diǎn)，提出了一種基于快速bp算法的神經(jīng)網(wǎng)絡(luò)自適應(yīng)模糊控制器，能夠?qū)ο到y(tǒng)進(jìn)行在線控制。最后將混合pid控制應(yīng)用于h型鋼連軋機(jī)張力系統(tǒng)中，實(shí)現(xiàn)微張力控制，仿真結(jié)果說明其較傳統(tǒng)pid具有更好的性能，同時(shí)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(duì)基于神經(jīng)網(wǎng)絡(luò)的非線性動(dòng)態(tài)系統(tǒng)自適應(yīng)控制方法進(jìn)行了深入研究,利用實(shí)驗(yàn)輸入輸出數(shù)據(jù)離線設(shè)計(jì)了動(dòng)態(tài)遞歸神經(jīng)網(wǎng)絡(luò)開環(huán)、閉環(huán)控制器,并分別采用基于神經(jīng)網(wǎng)絡(luò)的直接自校正控制方法與基于神經(jīng)網(wǎng)絡(luò)的間接自適應(yīng)控制方法對(duì)彈性連桿機(jī)構(gòu)實(shí)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(jī)控制系統(tǒng)采用自適應(yīng)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(xué)模型，并進(jìn)行了簡化和離散化；根據(jù)目前拉彎機(jī)控制系統(tǒng)的特點(diǎn)和存在的問題，第一次把極點(diǎn)配置自校正控制算法引入拉彎機(jī)控制系統(tǒng)中，為智能化拉彎機(jī)控制系統(tǒng)的研究和開發(fā)奠定了理論基礎(chǔ)。 - 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(yīng)控制理論應(yīng)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(yīng)控制、基于參數(shù)辨識(shí)的漸近跟蹤自適應(yīng)控制、極點(diǎn)配置的自校正控制和廣義預(yù)測(cè)的自適應(yīng)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(yīng)用單神經(jīng)元自適應(yīng)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(fù)載擾動(dòng)和參數(shù)時(shí)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(qiáng)。在分析單神經(jīng)元自適應(yīng)psd控制器特性后，本文提出用對(duì)角遞歸神經(jīng)網(wǎng)絡(luò)辯識(shí)控制對(duì)象，為psd控制器提供靈敏度參數(shù)，從而構(gòu)成一神經(jīng)網(wǎng)絡(luò)自校正控制方案。 - Expanding this algorithm , the thesis studies the possibility to utilize step - response identification in self - tuning control of non - minimum phase plant . suggestions above are examined by simulat ion with simulink toolbox in matlab environment . numerical examples of self - tuning pdf control running this algorithm are presented to compare the operational performance with the ordinary pdf scheme , showing effectiveness of the algorithm when implemented in practical use
本文還對(duì)上述算法進(jìn)行引伸，探討了對(duì)象為非最小相位時(shí)，用階躍響應(yīng)的輸出特性來對(duì)其進(jìn)行控制的可能性，以上各種設(shè)想均在matlab環(huán)境下，用simulink進(jìn)行仿真驗(yàn)證，并與預(yù)置系數(shù)pdf控制系統(tǒng)進(jìn)行比較，證明了所提出的方法具有良好的控制效果及實(shí)踐的可行性。