本文關(guān)鍵詞：基于智能優(yōu)化方法的永磁電機(jī)驅(qū)動(dòng)液壓動(dòng)力源控制策略研究　出處：《西安建筑科技大學(xué)》2014年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 液壓動(dòng)力系統(tǒng) 模糊邏輯 神經(jīng)網(wǎng)絡(luò) 遺傳算法 優(yōu)化控制

【摘要】：本文研究的液壓動(dòng)力系統(tǒng)采用永磁伺服電機(jī)帶動(dòng)齒輪泵作為液壓動(dòng)力源，不僅具備結(jié)構(gòu)簡(jiǎn)單、高可靠性、較寬調(diào)速范圍、高節(jié)能率的優(yōu)點(diǎn)，而且克服了傳統(tǒng)液壓系統(tǒng)結(jié)構(gòu)復(fù)雜、高能耗等諸多不足，容易實(shí)現(xiàn)閉環(huán)控制。目前在控制策略上仍然廣泛采用PID控制，由于液壓系統(tǒng)在負(fù)載變化時(shí)流量和壓力的強(qiáng)耦合特性，控制對(duì)象仍然具有不確定、時(shí)變和高度非線性[129]，采用簡(jiǎn)單PID線性控制器往往不能得到較好的控制性能。為此出現(xiàn)了多種先進(jìn)控制技術(shù)結(jié)合智能控制運(yùn)用到液壓系統(tǒng)中都取得好的控制效果。目前，由于智能控制的基礎(chǔ)理論發(fā)展仍不完善，所以各種智能控制方法的綜合應(yīng)用還存在許多需要我們改進(jìn)的地方。因此，本論文結(jié)合模糊邏輯、神經(jīng)網(wǎng)絡(luò)、遺傳算法、粒子群等優(yōu)化算法，旨在設(shè)計(jì)出能提高液壓動(dòng)力源控制品質(zhì)的控制器，并研究其參數(shù)優(yōu)化方法。具體創(chuàng)新點(diǎn)和研究工作包括以下內(nèi)容： (1)利用解析法對(duì)永磁交流伺服電機(jī)驅(qū)動(dòng)定量泵（液壓動(dòng)力源）進(jìn)行了數(shù)學(xué)建模。在分析永磁電機(jī)物理方程、轉(zhuǎn)矩方程及其基于坐標(biāo)變換的三環(huán)調(diào)節(jié)矢量控制系統(tǒng)的基礎(chǔ)上，用MATLAB的simulink搭建了永磁伺服電機(jī)驅(qū)動(dòng)定量泵的系統(tǒng)仿真模型，為后續(xù)章節(jié)控制系統(tǒng)的設(shè)計(jì)提供仿真平臺(tái)，為研究控制參數(shù)優(yōu)化算法提供理論支持。 (2)遺傳算法中如果交叉率及變異率保持不變，極易引起過(guò)早收斂、陷入局部極值等問(wèn)題，針對(duì)上述問(wèn)題提出了利用模糊控制器調(diào)整交叉率及變異率的遺傳參數(shù)自適應(yīng)調(diào)整算法，提高算法的收斂速度和獲得全局最優(yōu)解的能力。通過(guò)對(duì)永磁電機(jī)驅(qū)動(dòng)的液壓系統(tǒng)流量進(jìn)行常規(guī)優(yōu)化方法和改進(jìn)遺傳優(yōu)化方法控制的對(duì)比，仿真和實(shí)驗(yàn)結(jié)果表明：改進(jìn)遺傳優(yōu)化方法，可使系統(tǒng)在復(fù)雜工況下，保持良好的控制性能,并且具有較高的控制精度和魯棒性。 (3)由于實(shí)際的液壓系統(tǒng)參數(shù)存在時(shí)變性，，系統(tǒng)易受外界載荷的干擾，具有非線性、強(qiáng)耦合的特征，難以建立準(zhǔn)確的數(shù)學(xué)模型，針對(duì)上述問(wèn)題采用了粒子群結(jié)合BP混合優(yōu)化算法，優(yōu)化前向神經(jīng)網(wǎng)絡(luò)PID控制系統(tǒng)。該控制系統(tǒng)PID控制器參數(shù)可通過(guò)神經(jīng)網(wǎng)絡(luò)自學(xué)習(xí)調(diào)整，該控制策略較好的結(jié)合了粒子群優(yōu)化算法和BP算法的優(yōu)點(diǎn)，先用粒子群算法離線優(yōu)化后用BP算法在線優(yōu)化控制器參數(shù)。并將其運(yùn)用于永磁伺服電機(jī)驅(qū)動(dòng)的液壓系統(tǒng)中，仿真結(jié)果驗(yàn)證了該系統(tǒng)在各種典型工況下良好的動(dòng)靜態(tài)性能。 (4)智能控制方法的綜合應(yīng)用可以揚(yáng)長(zhǎng)避短、相得益彰。針對(duì)液壓系統(tǒng)的非線性、強(qiáng)耦合特征，本文采用了一種新的神經(jīng)網(wǎng)絡(luò)控制方法，融合了模糊控制、神經(jīng)網(wǎng)絡(luò)及PID控制各自的特征。將專家推理和神經(jīng)網(wǎng)絡(luò)的自學(xué)習(xí)功能相結(jié)合，使神經(jīng)網(wǎng)絡(luò)的性能更加完善，同時(shí)采用RBF網(wǎng)絡(luò)在線辨識(shí)，向神經(jīng)網(wǎng)絡(luò)控制器提供變化的梯度信息，進(jìn)一步提高系統(tǒng)的控制性能。對(duì)液壓動(dòng)力系統(tǒng)進(jìn)行了典型工況下的流量跟蹤控制仿真。仿真結(jié)果驗(yàn)證了本文的綜合控制方案優(yōu)于單一控制方法，系統(tǒng)的各項(xiàng)控制指標(biāo)均得到提高。 （5）在深入研究傳統(tǒng)PID控制和模糊控制原理的基礎(chǔ)上，分別實(shí)現(xiàn)了變頻調(diào)速液壓動(dòng)力源流量的實(shí)時(shí)在線控制。并結(jié)合具體的工況分析了傳統(tǒng)PID和模糊控制各自的特點(diǎn)，得出模糊控制在液壓系統(tǒng)正弦加載的工況下具有比PID控制更強(qiáng)的魯棒性的結(jié)論，較適合于載荷頻率變化較快的場(chǎng)合應(yīng)用。 （6）由于PID控制算法簡(jiǎn)單易行，大多數(shù)工業(yè)控制仍采用傳統(tǒng)PID控制，在具體應(yīng)用時(shí)存在一定缺陷,如：響應(yīng)快速和超調(diào)小很難同時(shí)達(dá)到最優(yōu)，所以在要求較高的場(chǎng)合PID控制不能滿足要求。針對(duì)上述問(wèn)題論文提出了模糊PID串聯(lián)復(fù)合控制策略，充分將模糊控制的快速性與PID控制精度高的特點(diǎn)相結(jié)合，實(shí)現(xiàn)了液壓動(dòng)力源流量的實(shí)時(shí)在線控制，實(shí)驗(yàn)結(jié)果表明：復(fù)合控制響應(yīng)快速、無(wú)超調(diào)、精度高，控制性能明顯優(yōu)于單一控制方法，適合控制要求較高的場(chǎng)合。
[Abstract]:The hydraulic power system is studied in this paper using permanent magnet servo motor drives the gear pump as the hydraulic power source, not only has the advantages of simple structure, high reliability, wide speed range, the advantages of high energy saving rate, and to overcome the traditional hydraulic system of complicated structure, high energy consumption and other shortcomings, to achieve closed-loop control. At present, the control strategy is still widely using PID control, due to the strong coupling characteristics of the hydraulic system flow and pressure changes in the load, control object is still uncertain, time-varying and nonlinear [129], using a simple PID linear controller often can not get good control performance. Therefore the emergence of a variety of advanced control technology combined with intelligent control theory is used to control the good effect get in the hydraulic system. At present, due to the development of the basic theory of intelligent control is still not perfect, the comprehensive application of intelligent control methods so there are various We need to improve the place. Therefore, this paper combines fuzzy logic, neural network, genetic algorithm, particle swarm optimization algorithm to design controller can improve the quality control of hydraulic power source, and to study the parameter optimization method. The innovation and research work includes the following contents:
(1) of the permanent magnet AC servo motor driven pump (hydraulic power source) using the analytic method of mathematical modeling. In the analysis of permanent magnet motor torque equations and physical equations, based on coordinate transformation of tricyclic regulation of vector control system, using MATLAB Simulink built the simulation model of constant pump permanent magnet servo motor drive the simulation platform provides for the design of control system for the following chapters, the parameters provide theoretical support for optimization control research.
(2) if the genetic algorithm crossover rate and mutation rate remained unchanged, extremely easy to cause the premature convergence problem into local extremum, aiming at the above problems by using fuzzy controller to adjust the crossover rate and mutation rate adaptive genetic algorithm parameters is proposed to improve the convergence speed and the ability to obtain the global optimal solution. The improved contrast control of genetic optimization method based on the flow of the hydraulic system of permanent magnet motor driven by conventional methods and optimization, simulation and experimental results show that the improved genetic optimization method, can make the system under complicated conditions, maintaining good control performance, and has high control precision and robustness.
(3) due to the presence of the hydraulic system parameters of practical time-varying system, vulnerable to interference, the external load is nonlinear, strong coupling characteristics, it is difficult to establish accurate mathematical model, aiming at the above problems using particle swarm optimization combining BP hybrid optimization algorithm, feedforward neural network PID control system. The control parameters of PID controller the system can through the neural network self-learning adjustment, the control strategy is a good combination of the advantages of particle swarm optimization algorithm and BP algorithm, using particle swarm optimization algorithm with off-line optimization optimization of controller parameters online. BP algorithm and applied to the hydraulic system of permanent magnet servo motor drive, the simulation results show that the system in the a variety of typical conditions good dynamic and static performance.
(4) the comprehensive application of the intelligent control method can avoid weaknesses and complement each other. According to the nonlinear hydraulic system, strong coupling characteristics, this paper proposes a new control method of neural network, combines fuzzy control, neural network and PID control of their respective characteristics. The self-learning function of combining expert reasoning and neural network. The performance of the neural network is more perfect, and the online identification of RBF network, to provide gradient information changes to the neural network controller, to further improve the control performance of the system. The typical working conditions of flow tracking control simulation of the hydraulic system. The simulation results verify the comprehensive control scheme is better than that of the single control method in this paper, the control indexes of the system are improved.
(5) based on in-depth research of traditional PID control and fuzzy control principle, realize real-time control of VVVF hydraulic power flow. Combined with the specific condition and analyzed the characteristics of traditional PID and fuzzy control, the fuzzy control has the robustness of control is stronger than PID in the hydraulic system of sine the loading conditions, suitable for load frequency fast changing situations.
(6) the PID control algorithm is simple, most industrial control is still using the traditional PID control, there are some defects in specific applications such as fast response and small overshoot is difficult to achieve optimal at the same time, so can not meet the requirements in the occasions with higher requirements for the PID control. The proposed fuzzy PID series composite the control strategy, and PID features fully fast fuzzy control precision high combination realizes real-time control of hydraulic power flow, the experimental results show that the composite control of fast response, no overshoot, high control precision, better performance than that of single control method for the control requirements of the occasion.

【學(xué)位授予單位】：西安建筑科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM351;TP271.31

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