【正文】 中文 4189 字 出處： Control Engineering Practice, 2020, 14(2): 137147 外文翻譯 學生姓名 學院名稱 機電工程學院 專業(yè)名稱 機 械 設計制造 及 其 自 動 化 指導教師 An experimental study on the optimization of controller gains for an electrohydraulic servo system using evolution strategies MY Kim, CO Lee Abstract This paper deals with an experimental optimization problem of the controller gains for an electrohydraulic position control system through evolution strategies (ESs)based method. The optimal controller gains for the control system are obtained by maximizing ?tness function designed specially to evaluate the system performance. In this paper, for an electrohydraulic position control system which would represent a hydraulic mill stand for the rollgap control in plate hotrollings, the time delay controller (TDC) is designed, and three control parameters of this controller are directly optimized through a series of experiments using this method. It is shown that the nearoptimal value of the controller gains is obtained in about 5th generation, which corresponds to approximately 150 experiments. The optimal controller gains are experimentally con?rmed by inspecting the ?tness function topologies that represent system performance in the gain spaces. It is found that there are some local optimums on a ?tness function topology so that the optimization of the three control parameters of a TDC by ma nual tuning could be a task of great dif?culty. The optimized results via the ES coincide with the maximum peak point in opologies. It is also shown that the proposed method is an ef?cient scheme giving economy of time and labor in optimizing the controller gains of ?uid power systems experimentally. Keywords: Controller gain optimization。 Evolution strategies。 Time delay control。 Automatic controller gain search。 Electrohydraulic servo system 1. Introduction Recently, the research on the optimization and adaptation of controller gains or parameters for improving the system performance in hydraulic and pneumatic servo systems has been a ?eld of increasing interest (Fleming amp。 Purshouse, 2020。 Klein, 1992。 Jeon, Lee, amp。 Hong, 1998。 Hyun amp。 Lee, 1998。 Choi, Lee, amp。Cho, 2020). In general, when control engineers design controller for hydraulic or pneumatic servo systems, it is very dif?cult to determine theoretically its control gains to exhibit the best performance of the systems, because the accurate modeling for these systems is hard due to highly nonlinear characteristics of the ?uid power systems. To be more speci?c, the hydraulic and pneumatic servo systems already have a relatively higher degree of nonlinearity than other mechatronic systems like DC or AC servo systems. It results from various factors (Merrit, 1976。 Watton, 1989): the pressure?ow characteristics of valve, the saturation of valve and cylinder, the leakage ?ow characteristics of valve and cylinder with variation of supply pressure, the friction characteristic in cylinder, the variation of viscosity and pressibility of working ?uid with the temperature, the ?ow characteristic due to the shape of pipeline, and most importantly, the variation of the system gains with the supply pressure and the load pressure. Therefore, when these ?uid power systems are controlled, the controller gains are adjusted on the foundation of expert’s intuitive knowledge about the system and the tuning experience of the controller gains in general. It needs very excessive experiments through trial and error. But though some controller gains are obtained, it is hard to say that the results are the best gain set at a given situation. For the automatic adjustment of the controller gains in ?uid power systems, the research to application of a fuzzy gain adapter (FGA) has been performed (Jeon, 1997。 Klein, 1992). In this case, the knowledge base is needed for transplantation of the expert knowledge to the systems, and some general rules to variation of the system response due to variation of the controller gains are demanded for the construction of this knowledge base. Therefore, much expert’s experiences and many experiments are necessary for the implementation of this algorithm. In this study, evolution strategies (ESs) is proposed as a method of the automatic optimization of the controller gains in a electrohydraulic system. ES is one of the evolutionary algorithms based on the natural geics and the survival of the ?tt