基于T-S 模糊模型的采样数据网络控制系统H∞ 输出跟踪控制

研究具有采样数据的基于T-S (Takagi-Sugeno) 模糊模型网络控制系统H输出跟踪控制问题. 提出将采集器端数据采样周期、数据传输时滞和数据丢包转换为零阶保持器端数据更新周期, 在此基础上, 利用输入时滞法和PDC (Parallel distributed compensation) 技术, 建立网络环境下被控对象和参考模型合并的基于T-S 模糊模型的增广系统模型. 通过Lyapunov 方法, 并充分利用采样特性, 给出系统实现H输出跟踪的充分条件, 以及可靠模糊控制器的设计. 仿真结果表明所设计模糊控制器能够实现该类系统良好的跟踪.     

基于多模型的动态矩阵控制

针对动态特性随工况而变化的复杂工业过程,本文提出一种基于多模型的动态矩阵控制。根据被控对象参数的变化范围建立多个模型,同时建立以模型输出误差为变量的具有积分特点的指标切换函数。在每一采样时刻根据指标函数与实际对象最接近的模型,并将基于此模型的控制器切换为当前控制器。仿真结果表明对多工况的控制令人满意。     

基于连续时间模型的多智能体系统采样数据一致性

讨论了一般线性模型的多智能体系统具有时变采样间隔的采样数据一致性问题.首先基于连续时间模型,利用采样数据的离散时间特性分析时变采样间隔允许的上界.由于不考虑采样间隔之间的状态,Lyapunov函数仅需要在每个采样时刻保证递减.由此得到了一个利用线性矩阵不等式求解更低保守性的时变采样间隔上界的方法.接着通过参数化矩阵变量得到了基于线性矩阵不等式的控制器设计方法.最后数值仿真展示了理论结果的正确性.     

模糊非脆弱动态输出反馈H∞控制器设计

本文考虑受有限字长影响的离散时间模糊系统的非脆弱H∞控制问题. 假定所设计的控制器具有加性区间型增益变量, 该增益变量反映了控制器数字执行过程中有限字长的影响. 区间型增益变量导致控制器设计具有数值计算问题, 而模糊性质的引入进一步增加了控制器设计的复杂性, 使问题变得更具有挑战性. 本文采用结构的顶点分离器方法来解决数值计算问题, 从而给出一个基于线性矩阵不等式的模糊非脆弱H∞控制器设计的两步算法. 该设计结果保证闭环系统渐进稳定并具有指定的H∞性能指标. 最后给出一个数值例子验证所提出方法的有效性.     

基于粒子群优化的室内动态热舒适度控制方法

针对预测平均投票数(predicted mean vote,PMV)值在舒适区和节能区之间周期性交替变化的控制方法,提出了基于PMV的动态舒适度冷/热抱怨模型和能耗模型.基于此模型,根据用户设定的舒适和节能两者的协调关系,运用改进的多目标离散粒子群优化算法,得出动态舒适度控制系统输入参数的寻优方法.该方法只需实时测量热环境和居住者热感觉数据,不需建立热环境物理解析模型,普适性强.实验证明了上述控制方法的有效性,该方法可实现动态舒适度的最优控制.     

多变量模糊系统控制设计及其在并行混合电动汽车中的应用

利用矩阵半张量积方法研究了多变量模糊系统模糊逻辑控制器的设计,并得到了若干新的结果.首先给出了模糊规则新的表示形式,基于该表示形式,构造了模糊逻辑控制器的结构矩阵,将复杂的模糊推理转变成了简单的代数等式.然后当模糊控制规则不完全时,建立了最小入度控制算法;当模糊控制规则不一致时,给出了相应的处理方法.最后将得到的结果应用到并行混合电动汽车(PHEV)能量管理和控制策略的模糊控制器设计.     

离散T-S模糊系统的部分状态反馈H∞控制

基于部分状态信息的控制器是一类特殊的静态输出反馈控制器,一般难以利用线性矩阵不等式工具求解.本文研究离散T-S模糊系统的部分状态反馈镇定及部分状态反馈H∞控制问题.通过引入松弛变量,将离散T-S模糊系统的部分状态反馈镇定问题转换成求解一组线性矩阵不等式（LMI）,并给出基于LMI的部分状态反馈H∞控制器设计方法.通过数值算例验证了所给方法的有效性.     

非线性系统广义模糊跟踪控制

研究一种给定 H∞ 模型参考跟踪特性的非线性系统的 T-S 广义模糊跟踪控制问题. 通过把一般的模糊模型等价变换到广义模糊模型, 引入了松弛变量, 并基于线性矩阵不等式 (LMI) 给出了新的 H∞ 跟踪控制器设计方法. 控制器参数在一组线性矩阵不等式中同时得到求解, 避免了原有方法分步求解的困难, 方法简单易行且具有鲁棒性. 两个算例表明了结论的有效性.     

磨煤机制粉系统解耦内模控制器的设计及仿真

本文针对工业过程中常见的多变量时滞耦合输入输出系统,基于内模控制结构提出了一种多变量解耦内模控制设计的方法,该方法设计的内模控制器同时具有解耦器和控制器的作用。其优点是能够实现标称系统输出响应之间的近似或完全解耦,并且改善了系统的大迟延的特性。并与PID对角矩阵解耦设计方法相对比,结果表明：解耦内模控制器设计方法有更好的鲁棒性。     

未知参数多变量线性系统自适应模糊广义预测控制

对未知参数多变量线性系统提出了自适应模糊广义预测控制方法.该方法直接用模糊逻辑系统组成的向量设计广义预测控制器,并基于广义误差向量估计值对控制器中的未知向量和广义误差估计值中的未知矩阵进行白适应调整.该方法不但能保证闭环系统所有信号有界,而且可使广义误差向量收敛到原点的一个邻域内.     

Multiple fuzzy model-based temperature predictive control for HVAC systems

In this paper, a multiple model predictive control (MMPC) strategy based on Takagi–Sugeno (T–S) fuzzy models for temperature control of air-handling unit (AHU) in heating, ventilating, and air-conditioning (HVAC) systems is presented. The overall control system is constructed by a hierarchical two-level structure. The higher level is a fuzzy partition based on AHU operating range to schedule the fuzzy weights of local models in lower level, while the lower level is composed of a set of T–S models based on the relation of manipulated inputs and system outputs correspond to the higher level. Following this divide-and-conquer strategy, the complex nonlinear AHU system is divided into a set of T–S models through a fuzzy satisfactory clustering (FSC) methodology and the global system is a fuzzy integrated linear varying parameter (LPV) model. A hierarchical MMPC strategy is developed using parallel distribution compensation (PDC) method, in which different predictive controllers are designed for different T–S fuzzy rules and the global controller output is integrated by the local controller outputs through their fuzzy weights. Simulation and real process testing results show that the proposed MMPC approach is effective in HVAC system control applications.     

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.     

插值算法在模糊控制中的应用与仿真研究

该文针对目前某些模糊控制系统在控制过程中精度比较低的问题，将模糊控制系统离线得到的模糊控制表与双线性插值算法结合起来，提出一种新的基于在线插值的模糊控制系统的设计方法，用此方法使模糊控制器输入、输出值保持连续变化，以此来克服控制器因输入输出量化所造成的调节死区与可能出现的稳态等缺点，从而来达到提高模糊控制系统控制精度的目的。在某舰船控制系统的仿真例子说明了此方法的有效性。     

Grey prediction on indoor comfort temperature for HVAC systems

This paper describes determination of indoor comfort temperature for efficiently Heating, Ventilating, and Air-Conditioning (HVAC) system under dynamical environment. Making occupants’ satisfaction on thermal comfort is still challenging by how the temperature setpoint of the fresh made-up air in conventional HVAC systems can be adapted properly (normally fixed) when surroundings changes in time. Essentially, being unknown ahead of time, the outdoor temperature is systematically predicted by grey prediction model in this work. The Adaptive Comfort Theory (ACT) model captures relation of the indoor comfort temperature to the outdoor temperature based on the survey data on thermal comfort in real occupants’ living environment. With the grey prediction model and the ACT model, the predicted indoor comfort temperature can be implemented as the comfort temperature reference for HVAC control systems. The experiment results show the viability of the proposed methodology for efficient HVAC control system.     

Dynamic output feedback control with output quantizer for nonlinear uncertain T‐S fuzzy systems with multiple time‐varying input delays and unmatched disturbances

The dynamic output feedback control problem with output quantizer is investigated for a class of nonlinear uncertain Takagi‐Sugeno (T‐S) fuzzy systems with multiple time‐varying input delays and unmatched disturbances. The T‐S fuzzy model is employed to approximate the nonlinear uncertain system, and the output space is partitioned into operating regions and interpolation regions based on the structural information in the fuzzy rules. The output quantizer is introduced for the controller design, and the dynamic output feedback controller with output quantizer is constructed based on the T‐S fuzzy model. Stability conditions in the form of linear matrix inequalities are derived by introducing the S‐procedure, such that the closed‐loop system is stable and the solutions converge to a ball. The control design conditions are relaxed and design flexibility is enhanced because of the developed controller. By introducing the output‐space partition method and S‐procedure, the unmatched regions between the system plant and the controller caused by the quantization errors can be solved in the control design. Finally, simulations are given to verify the effectiveness of the proposed method.     

DF控制器的设计方法研究

基于动态模糊集（Dynamic Fuzzy Sets）理论和动态模糊控制推理模型的相关概念,提出了一种DF控制器的设计方法,给出了DF控制器结构,探讨了DF控制规则库、DF控制推理计算、DF化以及清晰化方法,解决了控制过程中的动态模糊性问题,更符合具有动态模糊性特点的控制系统的控制规律,并通过具体的应用实例体现了此设计方法的有效性和可操作性.     

Robust Stabilization of Uncertain Fuzzy Systems Using Variable Structure System Approach

Based on the variable structure system (VSS) theory, we develop a fuzzy control system design method for a class of uncertain nonlinear multivariable systems that can be represented by a Takagi-Sugeno fuzzy model. We make the first attempt to relax the restrictive assumption that each nominal local system model shares the same input channel, which is required in the traditional VSS-based fuzzy control design methods. As the local controller we use a sliding mode controller with a switching feedback control term. In terms of linear matrix inequalities (LMIs), we derive a sufficient condition for the existence of linear sliding surfaces guaranteeing asymptotic stability of the reduced-order equivalent sliding mode dynamics. We present an LMI characterization of such sliding surfaces. We also give an LMI-based algorithm to design the switching feedback control term so that a stable sliding motion is induced in finite time. Finally, we give a numerical design example.     

基于模糊控制算法的纯电动汽车空调控制器的研发

纯电动汽车迅速发展,要求其空调系统也急需跟进。根据纯电动汽车特点,开发出一种纯电动汽车空调控制器系统,设计了空调控制器的电源模块,阐述了使用无位置传感器控制压缩机无刷直流电机的原理,研发了一种过流检测电路。提出了一种新型控制方法,即：在考虑整车负载的基础上,使用多输入变量模糊控制算法对汽车空调压缩机电机进行控制,同时兼顾了乘员的舒适性与汽车的动力性。结果表明这种空调控制器运行良好,达到了预期效果。     

基于模糊控制策略的车辆主动悬架研究

建立了车辆整车7自由度模型的主动悬架控制的系统状态方程模型,设计了两种模糊控制策略,方法一针对整车模型,采用一种控制方法,方法二针对整车模型的运动方式,设计不同的模糊控制器,垂直振动模糊控制器,俯仰振动模糊控制器,侧倾振动模糊控制器和逻辑控制器,仿真结果表明,所设计的模糊控制器对提高车辆的舒适性与操纵稳定性有较好的效果.     

一种基于T-S模糊模型的混沌控制方法

用T-S模糊系统来逼近非线性系统,它的IF-THEN规则后件由线性状态空间子系统构成,进而可以应用模糊系统的控制理论求得模糊控制器,用此非线性控制器来控制非线性系统,以求良好的控制效果;将模糊控制技术应用于混沌控制中,可以克服反馈线性化等传统方法对参数完全精确已知的限制;模糊规则后件部分以局部线性方程形式给出的T-S模糊模型可以通过调整相关参数很好地逼近混沌系统,基于该模型采用平行分散补偿技术设计出具有相同规则数目的模糊控制器,控制器所有参数可以通过求解一组线性矩阵不等式一次性得到。仿真结果验证了该方法的有效性。