本文關(guān)鍵詞： 城市明渠 遠(yuǎn)程監(jiān)控 動(dòng)態(tài)規(guī)劃 自適應(yīng)動(dòng)態(tài)規(guī)劃　出處：《浙江大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：水資源是重要的戰(zhàn)略性資源,而明渠是城市引排水系統(tǒng)中的重要組成部分,對(duì)水資源的科學(xué)管理、調(diào)度和利用有著深遠(yuǎn)的意義。所以,對(duì)明渠引排水系統(tǒng)進(jìn)行合理的建設(shè)和控制,以保證城市的供排水需求就顯得尤為重要。在硬件設(shè)施方面,我國的明渠引排水系統(tǒng)建設(shè)比較落后,大多數(shù)明渠泵站仍以人工值守的方式進(jìn)行控制。在研究方面,國內(nèi)外對(duì)明渠的相關(guān)研究多集中于水位、流量和容積上的控制,而忽略了與能耗相關(guān)的控制代價(jià)。另外,由于難以獲取精確的數(shù)據(jù),且存在降水等不確定性因素,大多數(shù)基于模型的控制算法難以在實(shí)際工程當(dāng)中應(yīng)用。本文針對(duì)這些問題進(jìn)行了相關(guān)研究。1.針對(duì)控制方式落后的人工值守泵站,本文設(shè)計(jì)了一個(gè)明渠引排水系統(tǒng)的遠(yuǎn)程監(jiān)控自動(dòng)化改造方案,闡述了設(shè)計(jì)方案中監(jiān)控系統(tǒng)的組織架構(gòu),具體介紹了中央監(jiān)控服務(wù)器中組態(tài)平臺(tái)、中轉(zhuǎn)數(shù)據(jù)庫平臺(tái)和ODBC數(shù)據(jù)鏈接的設(shè)計(jì)和建立流程。該方案最終在實(shí)際工程項(xiàng)目當(dāng)中得到了成功應(yīng)用,并達(dá)到了預(yù)期的效果。2.針對(duì)已知明渠模型和降水預(yù)測(cè)的情況,本文提出了一種改進(jìn)的單明渠在線動(dòng)態(tài)規(guī)劃控制算法,控制目標(biāo)是跟蹤目標(biāo)水位和減小與能耗相關(guān)的控制代價(jià)。改進(jìn)動(dòng)態(tài)規(guī)劃算法通過引入狀態(tài)反饋和滾動(dòng)更新等機(jī)制,減小降水預(yù)測(cè)誤差對(duì)系統(tǒng)帶來的影響。本文對(duì)改進(jìn)動(dòng)態(tài)規(guī)劃算法進(jìn)行了仿真,并設(shè)置了傳統(tǒng)動(dòng)態(tài)規(guī)劃方法作為對(duì)照,結(jié)果顯示改進(jìn)的動(dòng)態(tài)規(guī)劃算法在水位跟蹤和節(jié)能降耗方面有著更佳的表現(xiàn)。3.針對(duì)明渠模型未知和存在降水、城市排水等干擾的的情況,本文提出了一種在線運(yùn)行的多明渠自適應(yīng)動(dòng)態(tài)規(guī)劃控制算法,目的同樣是在跟蹤明渠目標(biāo)水位的同時(shí)減小與能耗相關(guān)的控制代價(jià)。本文設(shè)計(jì)的自適應(yīng)動(dòng)態(tài)規(guī)劃算法為一個(gè)閉環(huán)結(jié)構(gòu),包含執(zhí)行神經(jīng)網(wǎng)絡(luò)和評(píng)判神經(jīng)網(wǎng)絡(luò)兩個(gè)RBF神經(jīng)網(wǎng)絡(luò)。本文對(duì)自適應(yīng)動(dòng)態(tài)規(guī)劃算法進(jìn)行了仿真,并與傳統(tǒng)的PID算法進(jìn)行對(duì)比,結(jié)果表明自適應(yīng)動(dòng)態(tài)規(guī)劃在水位跟蹤和減小控制代價(jià)方面優(yōu)于傳統(tǒng)PID控制算法。
[Abstract]:Water resource is an important strategic resource, and open channel is an important part of urban drainage system, which has far-reaching significance for the scientific management, regulation and utilization of water resources. It is very important to construct and control the open channel drainage system reasonably in order to ensure the water supply and drainage demand of the city. In terms of hardware facilities, the construction of the open channel drainage system in our country is relatively backward. Most open channel pumping stations are still controlled by manual monitoring. In the research aspect, the research on open channel mostly focuses on the control of water level, flow rate and volume, while neglecting the control cost related to energy consumption. Because it is difficult to obtain accurate data, and there are uncertain factors such as precipitation, Most model-based control algorithms are difficult to be applied in practical projects. 1. In this paper, a remote monitoring and control automation reconstruction scheme of open channel drainage system is designed, and the organization structure of the monitoring system in the design scheme is expounded, and the configuration platform in the central monitoring server is introduced in detail. The design and establishment process of the transit database platform and ODBC data link. Finally, the scheme has been successfully applied in the actual project, and achieved the expected effect. 2. Aiming at the known open channel model and precipitation forecast, In this paper, an improved on-line dynamic programming control algorithm for single open channel is proposed. The control target is to track the target water level and reduce the control cost related to energy consumption. The improved dynamic programming algorithm introduces the mechanism of state feedback and rolling update. In this paper, the improved dynamic programming algorithm is simulated, and the traditional dynamic programming method is used as a comparison. The results show that the improved dynamic programming algorithm has better performance in water level tracking, energy saving and consumption reduction. In this paper, a multi-channel adaptive dynamic programming control algorithm for on-line operation is proposed. The aim is to reduce the control cost associated with energy consumption while tracking the target water level in the open channel. The adaptive dynamic programming algorithm designed in this paper is a closed loop structure. There are two RBF neural networks including executive neural network and critical neural network. This paper simulates the adaptive dynamic programming algorithm and compares it with the traditional PID algorithm. The results show that the adaptive dynamic programming is superior to the traditional PID control algorithm in water level tracking and reducing control cost.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP273;TP277;TU99

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本文編號(hào)：1547716