基于最优理论的模糊控制系统研究与应用  

Research and Application of Fuzzy Control System Based on Optimal Control Theory Compound

作　　者：张颖[1] 苏世卿[2] 

机构地区：[1]江苏食品药品职业技术学院机电工程系,江苏淮安223001 [2]新乡职业技术学院数控技术系,河南新乡453006

出　　处：《机床与液压》2016年第4期112-115,共4页Machine Tool & Hydraulics

基　　金：国家自然科学基金资助项目(50575041)

摘　　要：自模糊控制理论不依赖对象精确模型,能够对非线性时变复杂控制系统进行有效的控制,在电液压自动控制领域得到广泛应用,但是其智能水平、适应能力和稳定控制精度有待提高。针对智能模糊控制在电液压自动控制系统方面的优势,从模糊推理机制出发,提出将最优控制思想引入到模糊推理过程中的智能模糊控制系统,即将模糊控制推理与最优控制理论相结合,构建新的模糊推理方案,提高其对对象参数变化的敏感性。对该系统进行仿真并实验,结果表明:相比常规的模糊控制方案,所提出的最优模糊控制方案可实现控制系统更快的响应速度、精确的位置跟踪,同时对系统参数变化具有响应时间短、控制精度高的特点,应用在吊车控制系统上具有较高的控制精度。此外,该控制设计方案结构较为简单,易于工程实现。With self-adaptive fuzzy control theory don't rely on accurate model and can be used to build effective control to nonlinear and time-varying complex system,it is more and more widely used in electro-hydraulic automatic control areas. However the improvement of system performances including intelligent level,adaptive capacity and stable control accuracy is restricted. Because the intelligent fuzzy control possessed advantage in electro-hydraulic control systems,one control scheme combining optimal control theory and fuzzy control reasoning was proposed by building the new fuzzy reasoning scheme from fuzzy inference mechanism. MATLAB simulation results show that,compared with convention control schemes,the proposed optimum fuzzy control scheme can achieve more quick response speed and accurate position tracking,meanwhile this scheme has a short response time,high control accuracy with system parameter variations and is applied to the crane control system with high control precision. In addition,its structure is simple,therefore it is easy to be implemented in engineering.

关 键 词：模糊控制 模糊推理 最优控制理论 非线性系统 系统仿真 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]