本文選題：極值搜索控制 + 非線性系統(tǒng)�。� 參考：《電子科技大學(xué)》2017年碩士論文

【摘要】：科學(xué)發(fā)展、技術(shù)創(chuàng)新是時(shí)代進(jìn)步的標(biāo)簽,為了強(qiáng)大國(guó)家的軍事實(shí)力和經(jīng)濟(jì)實(shí)力,同時(shí)也為了豐富人們的生產(chǎn)生活,智能化信息化的發(fā)展便成了迫在眉睫的問題。設(shè)備工藝的創(chuàng)新來自于設(shè)備核心技術(shù)的不斷優(yōu)化,在多樣化的設(shè)備生產(chǎn)中,非線性系統(tǒng)則充斥著整個(gè)生產(chǎn)流程。因此如何優(yōu)化非線性系統(tǒng),最大化提高設(shè)備生產(chǎn)效率,始終是國(guó)內(nèi)外學(xué)者熱門研究問題之一。本論文提出了一種改進(jìn)的極值搜索控制算法,針對(duì)非線性系統(tǒng)的輸出量和參考輸入量參考軌跡未知的情況進(jìn)行優(yōu)化,目的在于使控制系統(tǒng)在該算法作用下能夠穩(wěn)定收斂到系統(tǒng)最優(yōu)值的同時(shí),進(jìn)一步提高原算法的優(yōu)化效率。國(guó)內(nèi)外針對(duì)非線性系統(tǒng)的優(yōu)化算法很多,但大部分優(yōu)化算法對(duì)于參考軌跡未知的非線性系統(tǒng)不適用。而極值搜索控制算法作為一種自適應(yīng)控制方法,同時(shí)也是一種基于非模型的實(shí)時(shí)優(yōu)化方法能夠解決這類非線性系統(tǒng)的優(yōu)化問題。因此本文基于極值搜索控制算法,設(shè)計(jì)了新的控制器,在通過霍爾維茨判據(jù)證明了整個(gè)控制系統(tǒng)的穩(wěn)定性后,選取了不同的非線性系統(tǒng)模型驗(yàn)證改進(jìn)算法的可靠性。本文首先分別針對(duì)單輸入單輸出的靜態(tài)系統(tǒng)和動(dòng)態(tài)系統(tǒng),采用改進(jìn)的牛頓極值搜索控制算法,在理論分析上證明改進(jìn)控制算法具有穩(wěn)定收斂性后,通過與原牛頓極值搜索控制算法的對(duì)比仿真實(shí)驗(yàn),實(shí)現(xiàn)了對(duì)單輸入單輸出系統(tǒng)的優(yōu)化目標(biāo),同時(shí)達(dá)到了提高原算法優(yōu)化效率的目的。其次,本文針對(duì)極值搜索控制算法會(huì)陷入局部最優(yōu)的局限性,設(shè)計(jì)了一種多峰值搜索控制算法,該優(yōu)化算法將極值搜索控制算法與自動(dòng)變輸入步長(zhǎng)的方式結(jié)合,能夠?qū)崿F(xiàn)將系統(tǒng)輸出收斂到全局最優(yōu)值的目的。同時(shí),通過模擬局部遮陰的光伏陣列,采用多峰值搜索控制算法實(shí)現(xiàn)了光伏陣列全局最大功率的跟蹤,體現(xiàn)了該優(yōu)化算法的可靠性。最后擴(kuò)充非線性系統(tǒng)的維數(shù),針對(duì)多變量系統(tǒng)即多輸入單輸出的非線性系統(tǒng),采用改進(jìn)的牛頓極值搜索控制算法,通過嚴(yán)格的算法穩(wěn)定性證明后,從與原算法的對(duì)比仿真結(jié)果可以看出,改進(jìn)的牛頓極值搜索控制算法同樣適用與多變量的非線性系統(tǒng),而且提高了原算法的優(yōu)化效率。
[Abstract]:The development of science and technology innovation are the label of the progress of the times. In order to enrich the military strength and economic strength of the powerful country and enrich the people's production and life, the development of intelligent information technology has become an urgent problem. The innovation of the equipment technology comes from the continuous optimization of the equipment core technology, and in the variety of equipment production, The linear system is full of the whole production process. Therefore, how to optimize the nonlinear system and maximize the production efficiency of the equipment is one of the hot research problems of the scholars at home and abroad. In this paper, an improved extreme search control algorithm is proposed, which is aimed at the output of the nonlinear system and the unknown reference trajectory of the reference input. The purpose of line optimization is to make the control system converge to the optimal value of the system under the action of the algorithm and improve the optimization efficiency of the original algorithm. There are many optimization algorithms for nonlinear systems at home and abroad, but most of the optimization algorithms are not applicable to the nonlinear systems with unknown reference trajectory. As an adaptive control method and a non model based real-time optimization method, the optimization problem of this kind of nonlinear system can be solved. Therefore, this paper designs a new controller based on the extremum search control algorithm. After proving the stability of the whole control system through the Holzer Witz criterion, different non lines are selected. The reliability of the improved algorithm is verified by the sexual system model. Firstly, the improved Newton extremum search control algorithm is adopted for the single input and single output static system and the dynamic system. On the theoretical analysis, it is proved that the improved control algorithm is stable and convergent, and the simulation experiments are compared with the original bull ton extremum search control algorithm. The goal of optimizing the single input and single output system is presented, and the aim of improving the optimization efficiency of the original algorithm is achieved. Secondly, in this paper, a multi peak search control algorithm is designed for the limitation of the extreme search control algorithm which will fall into the local optimal. The algorithm combines the extremum search control algorithm with the automatic variable input step length. In addition, it can achieve the goal of converging the output of the system to the global optimal value. At the same time, the global maximum power tracking of the photovoltaic array is realized by using the multi peak search and control algorithm by simulating the partially shaded photovoltaic array, and the reliability of the optimization algorithm is reflected. Finally, the dimension of the non linear system is expanded and the multivariable system is more lost. The improved Newton extremum search control algorithm is adopted for the nonlinear system entering the single output. After the rigorous proof of the stability of the algorithm, it can be seen from the comparison simulation results with the original algorithm that the improved Newton extremum search control algorithm is also applicable to the nonlinear system with multivariable, and the optimization efficiency of the original algorithm is improved.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP13

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