共查询到20条相似文献,搜索用时 93 毫秒
1.
研究汽车巡航控制系统中采用模糊控制.模糊控制中的隶属函数和模糊推理规则的选取专家或者技术人员的经验,但人工经验具有随机性和主观性,使得其控制性能往往达不到理想的效果.针对上述问题,采用一种基于遗传算法的模糊控制策略,利用遗传算法并对隶属函数和模糊推理规则进行优化,从而使隶属函数和模糊推理规则的确定摆脱了人为经验的局限,提高了模糊控制的自适应能力.实验结果表明优化后的控制器可以使汽车巡航系统取得较满意的效果. 相似文献
2.
3.
4.
对于实际模糊控制系统,由于在高级语言中模糊控制器程序实现比较复杂,因此引入模糊控制存在一定困难.介绍了一种在C语言应用程序中调用Maltab资源设计模糊控制应用程序的方法,即利用Madab Fuzzy Logic工具箱中的独立C代码模糊推理引擎函数库,在C语言应用程序中,调用Mathb Fuzzy Logic工具箱建立的模糊推理系统数据文件(*.fis),从而得到能独立运行的C语言模糊控制应用程序.有效地降低了实际模糊控制系统的软件设计工作量,具有很好的应用前景. 相似文献
5.
6.
7.
近些年来,模糊控制发展很快,是很值得研究的方向,围绕模糊控制系统的实现过程,有很多需要进一步研究解决的问题,如模糊控制的基础理论、模糊学习、模糊推理等等,本文综述模糊控制实现过程中的有关问题。 相似文献
8.
《计算机科学与探索》2016,(10):1469-1474
模糊推理是模糊控制的核心问题,还原性则是评价模糊推理算法好坏的重要标准之一。在正则蕴涵算子的统一框架下,给出了基于模糊推理SIS(subsethood infer subsethood)算法的模糊取式(fuzzy modus ponens,FMP)问题解的统一表达式;基于SIS算法为模糊拒取式(fuzzy modus tollens,FMT)问题提出了一种改进的求解原则,并给出了FMT问题解的统一形式;证明了SIS FMP算法和SIS FMT算法均满足无条件还原性,讨论了FMP问题及FMT问题基于SIS算法的λ-水平解。该算法将为模糊控制领域提供更多可供选择的模糊推理方法。 相似文献
9.
10.
自适应模糊控制器设计 总被引:3,自引:1,他引:2
张松兰 《自动化技术与应用》2009,28(2):12-14
介绍了模糊控制的原理和模糊控制系统的设计方法,并MATLAB语言对模糊控制系统进行仿真。具体叙述了模糊集和模糊论域及隶属函数的确立、模糊控制规则的建立和模糊推理和去模糊化,阐释了模糊控制器在MATLAB中的具体实现方法,最后通过一个实例进行了仿真说明利用MATLAB语言使模糊控制系统设计和仿真变得容易、直观且迅速。 相似文献
11.
廉师友 《计算机工程与应用》2000,36(9):72-74
文章把语言值规则(模糊规则)视为语言值及其程度(隶属度)之间的一种对应关系,提出了程度函数和程度规则的概念,并由此建立了一种称为程度推理和程度控制的推理与控制方法。采用程度推理和程度控制,传统的模糊推理就变为简单的符号推演和函数计算,传统的模糊控制由数值/(语,度)转换、(语,度)变换和(语,度)/数值转换等三步来实现。 相似文献
12.
针对控制系统中对象的模糊性和动态性,基于动态模糊集(Dynamic Fuzzy Sets)及动态模糊逻辑(Dynamic FuzzyLogic)系统理论,给出DF控制推理模型的相关概念,如DF向量、DF语言变量、DF语言规则和DF蕴涵关系等,并在此基础上探讨基于DF语言规则的DF推理方法,最后通过实例说明这些概念和方法的应用。 相似文献
13.
Kai-Yuan Cai Lei Zhang 《Fuzzy Systems, IEEE Transactions on》2008,16(3):600-614
Different from the dominant view of treating fuzzy reasoning as generalization of classical logical inference, in this paper fuzzy reasoning is treated as a control problem. A new fuzzy reasoning method is proposed that employs an explicit feedback mechanism to improve the robustness of fuzzy reasoning. The fuzzy rule base given a priori serves as a controlled object, and the fuzzy reasoning method serves as the corresponding controller. The fuzzy rule base and the fuzzy reasoning method constitute a control system that may be open loop or closed loop, depending on the underlying reasoning goals/constraints. The fuzzy rule base, the fuzzy reasoning method, and the corresponding reasoning goals/constraints define the three distinct ingredients of fuzzy reasoning. While various existing fuzzy reasoning methods are essentially a static mapping from the universe of single fuzzy premises to the universe of single fuzzy consequences, the new fuzzy reasoning method maps sequences of fuzzy premises to sequences of fuzzy consequences and is a function of the underlying reasoning goals/constraints. The Monte Carlo simulation shows that the new fuzzy reasoning method is much more robust than the optimal fuzzy reasoning method proposed in our previous work. The explicit feedback mechanism embedded in the fuzzy reasoning method does significantly improve the robustness of fuzzy reasoning, which is concerned with the effects of perturbations associated with given fuzzy rule bases and/or fuzzy premises on fuzzy consequences. The work presented in this paper sets a new starting point for various principles of feedback control and optimization to be applied in fuzzy reasoning or logical inference and to explore new forms of reasoning including robust reasoning and adaptive reasoning. It can be also expected that the new fuzzy reasoning method presented in this paper can be used for modeling and control of complex systems and for decision-making under complex environments. 相似文献
14.
本文在基于汽车驾驶模拟器的自适应前照灯系统(Adaptive Front-Lighting System,AFS)半实物硬件仿真平台上,根据AFS动力学模型的特性,提出一种基于模糊PID控制的AFS步进电机控制方法。该方法以AFS动力学模型输出为输入,利用实验获得的经验人为创建语言控制规则,并依据其进行模糊推理,构成模糊规则表,计算模糊关系最终获得模糊输出判决。在实验中运用MATLAB工具将模糊PID算法和常规PID算法进行对比,并在AFS半实物仿真平台上进行性能分析。实验结果表明,模糊PID算法明显优于常规PID算法,且更适合AFS系统中步进电机的控制需求。 相似文献
15.
In this paper, we present a weighted fuzzy interpolative reasoning method for sparse fuzzy rule-based systems, where the antecedent variables appearing in the fuzzy rules have different weights. We also present a weights-learning algorithm to automatically learn the optimal weights of the antecedent variables of the fuzzy rules for the proposed weighted fuzzy interpolative reasoning method. We also apply the proposed weighted fuzzy interpolative reasoning method and the proposed weights-learning algorithm to handle the truck backer-upper control problem. The experimental results show that the proposed fuzzy interpolative reasoning method using the optimally learned weights by the proposed weights-learning algorithm gets better truck backer-upper control results than the ones by the traditional fuzzy inference system and the existing fuzzy interpolative reasoning methods. The proposed method provides us with a useful way for fuzzy rules interpolation in sparse fuzzy rule-based systems. 相似文献
17.
18.
《Fuzzy Systems, IEEE Transactions on》2009,17(6):1412-1427
19.
20.
针对传统模糊推理算法在推理过程中容易忽略部分推理信息,模糊规则一旦确定就难以调整的缺点,提出一种基于数值计算的模糊推理算法。算法采用数值计算的方法对推理过程进行了改进,这种改进能够充分考虑所有输入的影响,又能根据输入的变化,对模糊规则进行适当的调整。基于该算法的模糊控制器能够大大提高控制性能和精度,减小稳态误差。通过对直流电动机的仿真控制效果表明,该控制器比传统模糊控制器的控制性能好,精度高,抗干扰能力强。 相似文献