本文選題：數(shù)據(jù)驅(qū)動控制 + 迭代學(xué)習(xí)控制　； 參考：《青島科技大學(xué)》2017年碩士論文

【摘要】：許多的工業(yè)生產(chǎn)過程是受輸入或輸出范圍限制的,針對此類受限系統(tǒng),本論文提出了基于數(shù)據(jù)的受限最優(yōu)迭代學(xué)習(xí)控制(constrained-DDOILC)方案,論文的主要工作及創(chuàng)新點如下:1)對傳統(tǒng)的受限最優(yōu)迭代學(xué)習(xí)控制(OILC)方法進(jìn)行了分類整理,受限范圍分為輸入受限、輸出受限和輸入輸出受限三方面,同時討論了當(dāng)控制系統(tǒng)中存在不確定參數(shù)時所采用的控制方法。2)針對一類帶輸入輸出約束的非線性離散時間系統(tǒng)提出了constrained-DDOILC控制方案,該方案不需要任何的模型信息,僅僅利用I/O數(shù)據(jù)。通過引入一種新的迭代動態(tài)線性化方法,利用二次規(guī)劃的最優(yōu)控制工具,考慮I/O受限條件來進(jìn)行設(shè)計。由于所提方案是數(shù)據(jù)驅(qū)動的,無需建模,因而設(shè)計過程中不存在未建模動態(tài)等問題,同時可以保證被控系統(tǒng)的魯棒性,本文首先提出基于Lifted的技術(shù)進(jìn)行控制設(shè)計,利用控制實例對其進(jìn)行了仿真驗證。3)針對同樣的帶輸入輸出約束的非線性離散時間系統(tǒng),把基于Lifted技術(shù)的控制方案推廣到Non-lifted技術(shù)上,并進(jìn)行了相應(yīng)的收斂性證明和仿真驗證。4)針對工業(yè)生產(chǎn)過程中存在的多點跟蹤問題,論文提出了基于數(shù)據(jù)的受限最優(yōu)點對點迭代學(xué)習(xí)控制(constrained-DDOPTPILC)方案,該方案只需利用特定點的誤差信息,跟蹤給定系統(tǒng)期望的某一個或某幾個點。此種方案大大減小了計算量,減輕了產(chǎn)業(yè)成本,提高了工作效率。通過與傳統(tǒng)方法的仿真對比,進(jìn)一步驗證了所提方法的控制有效性。
[Abstract]:Many industrial processes are limited by input or output. In this paper, a constrained optimal iterative learning control scheme based on data is proposed for such constrained systems. The main work and innovation of this paper are as follows: (1) the traditional constrained optimal iterative learning control (OILC) method is classified. The restricted range is divided into three aspects: input constraint, output limitation and input / output limitation. At the same time, the control method. 2) for a class of nonlinear discrete-time systems with input and output constraints, a control scheme of constrained DDOILC is proposed, which does not require any model information. Using only I / O data. By introducing a new iterative dynamic linearization method and using the optimal control tool of quadratic programming, I / O constrained conditions are considered to design. Because the proposed scheme is data-driven and does not need to be modeled, there are no problems in the design process, such as unmodeled dynamics, and the robustness of the controlled system can be guaranteed at the same time. A simulation example is used to validate the proposed method. 3) for the same nonlinear discrete time system with input and output constraints, the proposed control scheme based on the lifted technique is extended to the Non-lifted technology. The corresponding convergence proof and simulation verification. 4) aiming at the multi-point tracking problem in industrial production process, a data-constrained optimal point-to-point iterative learning control scheme named constrained DDOPTPILC is proposed in this paper. The scheme only needs to use the error information of a given point to track one or more expected points of a given system. This scheme greatly reduces the calculation amount, reduces the industrial cost and improves the working efficiency. The control effectiveness of the proposed method is further verified by comparison with the traditional method.
【學(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP273

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本文編號：2005898