帆船的模糊自适应控制方法研究

针对非线性、时变的帆船航行系统,提出了一种基于T-S模糊模型的帆船模糊自适应控制新方法.该方法采用T-S模糊模型,将舵角的非线性控制局部线性化,设计相应的局部线性控制器,通过模糊推理综合各局部线性控制器的输出,得到全局控制量.利用线性神经网络技术的自学习技术,获取模糊推理规则,优化模糊控制器的参数,提高系统的自适应性.仿真结果表明,该方法能实现对帆船航向的智能控制,具有一定的实际应用价值.     

模糊预测控制在非线性时滞系统中的应用

针对工业控制系统中的非线性、时滞两大难题,结合预测控制中典型的动态矩阵控制(DMC)算法对时滞、模型失配、畸变、干扰等引起的不确定性能够及时得到弥补的优点以及T-S模糊模型对非线性系统良好描述的特性,将模糊控制与预测控制有机结合起来,根据被控对象工作点的变化实时选择模糊规则所对应的阶跃响应模型向量,结合DMC控制算法得到最优控制量,将基于线性系统建模的预测控制应用于非线性时滞系统控制中.     

Linearization of T-S fuzzy systems and robust H_∞ control

Takagi-Sugeno (T-S) fuzzy model is difficult to be linearized because of membership functions included. So, novel T-S fuzzy state transformation and T-S fuzzy feedback are proposed for the linearization of T-S fuzzy system. The novel T-S fuzzy state transformation is the fuzzy combination of local linear transformation which transforms local linear models in the T-S fuzzy model into the local linear controllable canonical models. The fuzzy combination of local linear controllable canonical model gives controllable canonical T-S fuzzy model and then nonlinear feedback is obtained easily. After the linearization of T-S fuzzy model, a robust H _∞ controller with the robustness of sliding model control (SMC) is designed. As a result, controlled T-S fuzzy system shows the performance of H _∞ control and the robustness of SMC.     

基于T-S模型的自适应模糊预测函数控制

针对多变量非线性系统，提出一种基于Takagi-Sugeno(T-S)模型的自适应模糊预测函数控制方法.在T-S模糊模型结构已确定情况下，利用加权递推最小二乘法对T-S模糊模型后件参数进行在线辨识.对模糊模型在每一采样点进行线性化，将描述非线性系统的T-S模型转化为线性时变的状态空间模型，并假设输入基函数为阶跃函数，推导出预测控制律的解析式.仿真结果表明，该方法在求解控制律时，无需求解非线性优化问题，并且有效克服了模型失配对系统控制性能的影响，增强了系统的跟踪性能和鲁棒性.     

基于T-S模型的非线性系统控制方法

采用T-S模糊模型逼近非线性系统,将非线性系统描述为多个局部线性系统的组合,采用极点配置的方法对每一局部线性系统进行设计,保证了局部线性系统的性能指标。利用线性矩阵不等式方法,将闭环控制系统的稳定条件、控制性能指标统一到线性矩阵不等式的框架内,通过求解线性矩阵不等式族获得控制器参数。以倒立摆系统为例,对提出的设计方法进行了验证,仿真结果表明设计方法是有效的。     

基于改进T-S模型的热工过程模糊辨识算法

提出了一种实用的基于T-S模型的热工系统模糊辨识方法。采用启发性知识与复合非线性优化方法相结合的综合方法求解出模糊模型的结构,然后通过基于熵的聚类和竞争学习算法对热工过程的输入数据空间进行划分,在此基础上利用递推最小二乘辨识算法建立一个热工过程的T-S模型。文中给出了熟知的Box-Jenkins数据的辨识结果,并将该方法应用于辨识单元机组的协调控制系统。     

基于T-S模糊模型的直接自适应预测控制

提出一种基于T-S模糊模型的直接自适应预测控制算法。该算法利用加权递推最小二乘法在线辨识T-S模糊模型的后件参数。用已经辨识好的参数,进行直接迭代计算,直接得到模型的预测输出。此算法很好地解决了非线性预测控制中,建模与优化两大难题,为非线性系统的高精度控制提供了保证。计算机仿真表明,该算法具有较好的跟踪性能。     

Robust State Feedback H∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model

T-S fuzzy model was applied to describe nonlinear system and global fuzzy model was expressed by the form of uncertain system. Based on robust state feedback H∞control strategy, designed a global asymptotic steady fuzzy model. This control system can use the experimental input-output data pairs for the biped robot learning and walking with dynamic balance. It is proved by simulation result that robust state feedback H∞ control method based on T-S fuzzy model can effectively restrain the effect of model uncertainties and external disturbance acting on biped robot. From these works, we showed the satisfactory performance of joint tracking without any chattering.     

基于T—S模型的不确定切换系统的鲁棒H∞可靠控制

提出一种基于局部T-S模型不确定切换系统的可靠控制方法,将输入空间划分为若干个区域,在每一区域内构建局部T-S模型并设计相应的控制器;这样由于模糊论域的变小而提高了逼近精度,然后再通过多模型切换控制,实现对整体非线性系统的逼近与控制．在此,利用并行分布补偿技术（PDC）,借助于LMI和凸优化方法,得出系统鲁棒凡可靠控制器的解析式．     

Adaptive predictive functional control based on Takagi-Sugeno model and its application to pH process

In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem, an adaptive fuzzy predictive functional control (AFPFC) scheme for multivariable nonlinear systems was proposed. Firstly, multivariable nonlinear systems were described based on Takagi-Sugeno (T-S) fuzzy models; assuming that the antecedent parameters of T-S models were kept, the consequent parameters were identified on-line by using the weighted recursive least square (WRLS) method. Secondly, the identified T-S models were linearized to be time-varying state space model at each sampling instant. Finally, by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established. The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015; the tracking ability of the proposed AFPFC is superior to that of non-AFPFC (NAFPFC) for pH process without disturbances, the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC; when the process parameters of AFPFC vary with time the integrated absolute error (IAE) performance index still retains to be less than 200 compared with that of NAFPFC.     

一类离散非线性不确定互联系统的模糊分散控制

对一类离散非线性不确定互联系统给出了模糊状态反馈分散控制设计的方法。设计中，首先采用模糊T—S模型对离散非线性不确定互联系统进行模糊建模，应用并行分布补偿算法(PDC)，给出分散反馈分散控制的设计。基于李亚普诺夫方法，给出了模糊闭环分散系统的稳定性分析。     

基于预测电压调制与T-S模糊PMLSM推力控制

为了进一步提高永磁直线同步电机(PMLSM)直接推力控制(DTC)系统的控制精度,提出了基于预测电压调制和Takagi-Sugeno(T-S)模糊策略的控制方法.利用预测电压调制技术控制下一个周期磁链,利用空间矢量脉宽调制技术(SVPWM)逼近预测电压值,采用T-S模糊控制器控制动子速度和电磁推力.对比分析在Matlab/Simulink环境下的仿真结果,基于预测电压调制和T-S模糊控制策略的DTC控制系统不仅明显减少电磁推力和磁链脉动,而且对电机参数时变等非线性扰动所引起的脉动具有较强的鲁棒性.     

基于T-S模糊建模思想的一类双人非线性非合作微分博弈的Nash均衡解

基于T-S模糊建模思想,利用T-S模糊建模方法,将一类双人非线性非合作微分博弈问题的模型转化为一个局部线性、整体非线性的T-S模糊系统,再利用其局部线性的特点,求出原问题的Nash均衡解的形式.     

Delay-dependent static output feedback control of nonlinear system

The static output feedback control problem for time-delay nonlinear system is studied based on T-S fuzzy bilinear model. The objective is to design a delay-dependent static output feedback controller via the parallel distributed compensation (PDC) approach such that the closed-loop system is delay-dependent asymptotically stable. A sufficient condition for the existence of such a controller is derived via the linear matrix inequality (LMI) approach and the design problem of the fuzzy controller is formulated as an LMI problem. The simulation examples show the effectiveness of the proposed approach.     

Robust non-fragile control for discrete-delay nonlinear large-scale systems

Time-delays,due to the information transmission between subsystems,naturally exist in large-scale systems and the existence of the delay is frequently a source of instability. This paper considers the problems of robust non-fragile fuzzy control for a class of uncertain discrete nonlinear large-scale systems with time-delay and controller gain perturbations described by T-S fuzzy model. An equivalent T-S fuzzy model is represented for discrete-delay nonlinear large-scale systems. A sufficient condition for the existence of such non-fragile controllers is further derived via the Lyapunov function and the linear matrix inequality( LMI) approach. Simulation results demonstrate the feasibility and the effectiveness of the proposed design and the proper stabilization of the system in spite of controller gain variations and uncertainties.     

非线性系统模糊平滑切换多模型控制

研究了一类可以平滑切换时刻输出跳变的多模型切换控制器的设计问题,基于T-S模糊模型提出一种非线性系统模糊平滑切换多模型控制,将输入空间划分为若干个模糊区域,使区域边界模糊化,在每一区域内设计局部T-S模型和控制器,从而使控制器切换在模糊了的边界处进行,保证了切换过程中系统状态轨迹的平滑性.仿真结果证明了方法的有效性.     

基于Fuzzy预测器的非线性网络控制系统的时延补偿

网络控制系统中时延是影响控制性能的一个主要因素，本文提出了一种基于Fuzzy预测器的非线性网络控制系统的时延补偿方法。首先通过输入输出缓冲使时延固定，然后以对象的数学模型为基础对时延进行预测，通过Fuzzy控制器、观测器和预测器得到经过时延补偿后的控制量，最后采用分离性定理证明了基于模糊观测器、预测器及控制器设计的闭环控制系统的稳定性。仿真结果验证了算法的有效性。     

不确定模糊系统的输出反馈控制

对一类不确定非线性系统利用模糊T-S模型进行建模，在此基础上提出了不确定模糊系统的输出反馈控制的设计。用矩阵不等式的形式给出了模糊系统可通过输出反馈控制的充分条件。通过引入辅助变量将矩阵不等式的条件转化为迭代线性矩阵不等式(LMI)，并给出了相应的算法，最后通过数值算例和仿真结果表明该算法的有效性。     

T-S模糊控制方法在生物流化床系统中的应用

针对生物流化床污水处理系统的非线性、时滞、时变等问题,提出采用T-S模糊控制方法,将复杂的非线性系统模糊化为局部线性模型,并引入积分环节,降低T-S模糊控制器维数,简化规则.最后,通过实验进行理论验证.实验结果表明,该方法可行且有效.     

一类带有时延的非线性网络控制系统的镇定

研究了一类非线性网络控制系统的镇定问题。利用一种新方法描述通讯网络有限传输能力所导致的时延,由T-S模糊模型和平行分布补偿技术建立了带有时延的非线性网络控制系统的模型。通过采用Lyapunov方法和线性矩阵不等式技术,得到了系统随机稳定的充分条件,并给出镇定控制器的设计方法。