基于梯形模糊数的不确定性河道生态需水模型及其应用

将模糊数引入河道生态需水估算方法中,建立了模糊生态流速和模糊生态水力半径的概念。以抛物线型过水断面河道为例,在扩展原理的基础上,建立了流量与模糊生态流速、模糊生态水力半径的函数关系,提出了基于梯形模糊数的不确定性河道生态需水模型,设计了算法流程。以杜柯河壤塘站为例进行研究,计算并给出了其不确定性河道生态需水量的结果。最后利用Tennant法对所建模型的实用性进行了验证,并对计算结果的表达形式进行了分析。结果表明本文方法得到的结果更合理,效果更好。     

基于主题深度搜索的数学领域教育平台研究

论文综合利用主题搜索技术、深网信息集成技术和Wiki技术,设计并实现了一个面向数学领域的教育平台.此平台是一个集数学资源共享和用户交流的开放平台,用户在此平台可以利用数学Wiki添加、编辑、评论数学领域信息,提升自主学习能力,实现广泛交流.同时,还能利用数学搜索引擎搜索到专业的数学知识,定制URL检索,扩大检索范围,提高了平台的个性化服务水平及搜索的准确率.实验结果表明,文中基于SVM分类算法的数学主题网页分类器具有较高的准确率和召回率.     

基于LSFD算法的小波模糊神经网络的研究与应用

利用小波变换的多分辨率特性构造小波模糊神经网络模型,并应用在非线性系统的辨识上.在参数学习上,给出了模糊微分与李亚普诺夫稳定相结合的新算法—LSFD算法,并与梯度下降法进行了对比.通过仿真,结果表明小波模糊神经网络模型与模糊神经网络、模糊小波神经网络、小波神经网络和神经网络等模型相比,其性能指标最小,收敛速度更快,更加准确.     

永磁同步电机模糊PID控制建模与仿真

永磁同步电机（PMSM）作为一种非线性、强耦合、参数时变的被控对象,传统PID对其控制效果欠佳。为此在PID的基础上,结合模糊控制的优点,设计了一种PMSM的模糊自适应PID控制策略,并对系统建模仿真。结果表明,与PID控制相比,该模糊PID控制方案具有自适应强、超调量小等特点。     

Adaptive type-2 fuzzy sliding mode controller for SISO nonlinear systems subject to actuator faults

In this paper, an adaptive type-2 fuzzy sliding mode control to tolerate actuator faults of unknown nonlinear systems with external disturbances is presented. Based on a redundant actuation structure, a novel type-2 adaptive fuzzy fault tolerant control scheme is proposed using sliding mode control. Two adaptive type-2 fuzzy logic systems are used to approximate the unknown functions, whose adaptation laws are deduced from the stability analysis. The proposed approach allows to ensure good tracking performance despite the presence of actuator failures and external disturbances, as illustrated through a simulation example.     

Adaptive fuzzy sliding mode power system stabilizer using Nussbaum gain

Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus （SMIB） and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.     

Variable Structure Control with Chattering Reduction of a Generalized T‐S Model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non‐linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi‐Sugeno (T‐S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T‐S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T‐S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T‐S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T‐S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC‐VSC shows that both alleviation of chattering and robust performance are achieved.     

Variable Structure Control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven infront of disturbances and noise effects.     

模糊PID和Hopfield神经网络在矿井通风系统中的应用

针对传统的PID控制或者单一的模糊控制无法准确控制矿井通风系统风量的问题,提出了一种采用模糊PID调节器和Hopfield神经网络调节器对矿井通风机的转速、风门、风量进行控制的方法。该方法利用模糊控制器对PID参数进行实时修正,并结合Hopfield神经网络的联想记忆功能和反馈调节特性,实现矿井通风机风量的快速、稳定输出。仿真与实验结果表明,模糊PID调节器和Hopfield神经网络调节器可以准确控制矿井通风机的转速和风量,实现通风系统的稳定输出。