一种模糊PID控制器的鲁棒优化设计

主要研究一种模糊PID控制器的鲁棒设计。以小增益定理分析得到该模糊PID控制系统稳定条件。针对参数摄动系统的‘最坏点’用该稳定条件作为约束,采用遗传算法对标称系统的性能进行优化,求得优化鲁棒控制器。同时对鲁棒模糊PID控制器中模糊非线性控制进行了比较分析。     

一类不确定参数混沌系统的鲁棒跟踪控制

提出了一种新型的鲁棒跟踪控制方法实现对一类不确定混沌系统的跟踪控制.基于李亚普诺夫稳定性理论,设计了一种能根据不同的应用环境方便地进行调整的鲁棒跟踪控制器.只要参数的不确定性是有界的,这种控制器就可以使混沌系统的状态向量跟踪期望轨迹.对R(o)ssler和Lorenz混沌系统的仿真结果验证了这种控制器是有效的.     

非线性系统基于T-S模型的鲁棒二次稳定控制

基于模糊动态模型研究非线性系统的稳定控制问题，将全局模糊系统模型表示成不确定系统形式。采用鲁棒二次稳定控制器设计方法，设计使全局模糊系统渐近稳定的控制器，避免了并行分配补偿法中求解公共矩阵P的困难。通过一级倒立摆的模糊控制器设计实例，证明了方案的简洁有效。     

含有恒功率负荷的直流微网鲁棒非脆弱模糊控制

当具有恒功率特性的负荷与源侧换流器级联时,会降低直流微网系统的阻尼,带来稳定性问题。针对上述问题,采用TS模糊模型,对含恒功率负荷的非线性直流微网系统进行建模。为有效抵抗直流微网和控制系统参数的不确定性,设计了一种鲁棒非脆弱控制器,在计算参数不确定矩阵的基础上,推导以线性矩阵不等式表示的Lyapunov指数稳定条件。经Matlab/Simulink仿真测试,所设计控制器满足直流微网对于稳定性的要求,能够提高闭环系统的暂态性能,对系统及控制器内部的不确定性拥有较强的鲁棒性。     

不确定分布式时滞系统的鲁棒H∞状态反馈控制

针对一类不确定分布式时滞系统的鲁棒H∞控制问题，采用线性矩阵不等式的方法通过选择适当的lyapunov函数，得到了自治系统的鲁棒渐进稳定的充分条件。推导出了闭环系统鲁棒渐近稳定的充分条件，并设计了无记忆性H∞状态反馈控制器，使得对于所有允许的不确定性，闭环系统鲁棒渐近稳定且具有给定的H∞性能指标。给出了控制器存在时滞相关的充分条件，且控制器参数能够通过求解线性矩阵不等式得到，对于一个高阶的数值仿真系统，通过对线性矩阵不等式的求解可以得到最优H∞性能指标，及相应不等式的解。仿真证明了该设计方案的有效性。     

基于发电单元完整模型的backstepping控制

针对发电单元高阶非线性完整数学模型(锅炉、汽轮机和发电机模型),结合系统参数的不确定性,采用backstepping动态面控制方法设计了一种鲁棒自适应控制器。在反推设计过程中引入了虚拟控制器和一阶低通滤波器,从而避免了对模型非线性进行多次微分而引起的算法复杂性,使设计方法简化。理论分析和仿真结果均表明,该控制器能够保证闭环系统的半全局渐近稳定性,对系统参数的不确定性具有较强的鲁棒性,在系统发生故障时能够使系统稳定运行。     

非线性系统模糊间接自适应控制的后推设计

采用模糊神经网络作为非线性逼近器，针对一类一阶非线性多入多出系统，提出了一种具有扰动抑制的鲁棒自适应控制方法，给出了高阶多入多出系统具有扰动抑制的自适应后推(backstepping)设计方法。在鲁棒项合理简化的情况下，给出了系统Lyapunov意义下的稳定性证明，简略分析了各设计参数的物理意义及其对系统性能的影响。理论分析和仿真实验均显示，本方法可以保证系统的全局渐近稳定性，且若选取恰当的设计参数可保证系统对输入信号的跟踪达到任意精度；由于鲁棒项的引入可使系统的设计更具灵活性。     

自适应滑模控制具有状态和输入时滞的不确定系统

针对一类对象模型具有非匹配不确定性,且同时具有状态时滞和输入时滞的线性系统,基于LMI方法,提出了系统存在滑动模态时滞相关的充分条件,考虑到在处理输入时滞时引入了未知扰动,进一步设计了对扰动参数具有自适应估计能力自适应滑模控制器,该方法保证了闭环系统鲁棒渐近稳定。仿真结果进一步证实了该控制策略的可行性。     

永磁同步电机混沌系统鲁棒非脆弱模糊H∞控制

为了探讨一类具有不确定参数的非线性系统T-S模糊模型,采用并行分布补偿策略,设计了两种带有不确定控制增益的模糊控制器。利用Lyapunov稳定性理论和矩阵理论,采用线性矩阵不等式(LMI)的处理方法,给出了存在非脆弱模糊控制器且满足鲁棒H∞性能指标的充分条件。用满足这一条件的控制器来控制永磁同步电机(PMSM)混沌系统,选择实际中可行的交轴电压作为控制变量,使系统不仅对控制增益的变化有非脆弱性,而且当系统存在扰动时,该控制器设计方法也能很好的抑制干扰。     

变速变桨距风电系统的功率水平控制

为实现风电系统的功率水平控制,该文基于奇异摄动理论和逆系统方法设计了一种非线性桨距角鲁棒控制器。该控制器由逆系统标称部分和鲁棒补偿部分组成,逆系统标称控制器可以使非仿射型非线性标称风机模型的输入-输出动态跟踪其参考模型动态;鲁棒补偿输入可以消除参数不确定性、风速检测误差和发电机转矩扰动对系统输出功率的影响。理论分析和仿真实验证明了该控制器的稳定性,结果表明,该控制器可以在风速波动时有效控制风电系统的输出功率水平,并且对参数化和非参数化扰动具有较强的鲁棒性。     

Robust nonlinear control of wind energy conversion systems

This paper presents stability analysis for a class of uncertain nonlinear systems and a method for designing robust fuzzy controllers to stabilize the uncertain nonlinear systems. First, the Takagi–Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the uncertain nonlinear system. Next, new stability conditions for a generalized class of uncertain systems are derived from robust control techniques such Linear Matrix Inequalities (LMIs). The derived stability conditions are used to analyze the stability of Takagi and Sugeno’s fuzzy control systems with uncertainty which can be regarded as a generalized class of uncertain nonlinear systems. The design method employs the so-called Parallel Design Approach (PDA). TS fuzzy systems are classified into three families based on the input matrices and a robust fuzzy controller’s synthesis procedure is given for each family. In each family, sufficient conditions are derived for robust stabilization in the sense of Taylor series stability, for the TS fuzzy system with parametric uncertainties. Important issues for the stability analysis and design are remarked. The effectiveness of the proposed controller design methodology is finally demonstrated through the two different models of Wind Energy Systems (WES) to illustrate the effectiveness of the proposed method.     

具有不确定参数的混沌系统的模糊保代价控制

研究了具有不确定参数混沌系统的稳定模糊保代价控制问题。采用T-S模糊模型描述混沌非线性系统，对具有范数有界，时变参数不确定性的混沌系统，得到了存在稳定模糊保代价控制器的充分条件。并推算出了相应的线性矩阵不等式(LMI)形式。     

基于T-S模型的模糊控制器设计

讨论了一类由T-S模糊模型表示的不确定时滞非线性系统的模糊控制器设计问题。刻画了系统的不确定性,采用并行分布补偿的基本思想设计了状态反馈控制器,分析了现有T-S型模糊控制器设计方法计算复杂且难以求解的原因,在此基础上,提出了一种与系统实时输入相关的动态模型简化算法。同时,利用Lyapunov稳定性理论和线性矩阵不等式等有关工具,得出了该不确定时滞非线性系统的稳定条件,并给出了系统以衰减率α全局渐近稳定的充分条件,从而相应得出T-S型模糊状态反馈控制器。仿真实例表明,该设计方法的有效性。     

Composite learning fuzzy synchronization for incommensurate fractional‐order chaotic systems with time‐varying delays

This paper presents a composite learning fuzzy control to synchronize two different uncertain incommensurate fractional‐order time‐varying delayed chaotic systems with unknown external disturbances and mismatched parametric uncertainties via the Takagi‐Sugeno fuzzy method. An adaptive controller together with fractional‐order composite learning laws is designed based on both a parallel distributed compensation technology and a fractional Lyapunov criterion. The boundedness of all variables in the closed‐loop system and the Mittag‐Leffler stability of tracking error can be guaranteed. T‐S fuzzy systems are provided to tackle unknown nonlinear functions. The distinctive features of the proposed approach consist in the following: (1) a supervisory control law is designed to compensate the lumped disturbances; (2) both the prediction error and the tracking error are used to estimate the unknown fuzzy system parameters; (3) parameter convergence can be ensured by an interval excitation condition. Finally, the feasibility of the proposed control strategy is demonstrated throughout an illustrative example.     

Robust Frequency Control in an Autonomous Microgrid: A Two-Stage Adaptive Fuzzy Approach

Highly intermittent power from renewable energy sources (RES) along with load and system perturbations in an autonomous microgrid (MG), results in large frequency fluctuations. Conventional controllers like PI controllers to be unable to provide acceptable performance over a wide range of operating conditions. To overcome this problem, present paper introduces a novel two-stage adaptive fuzzy logic based PI controller for frequency control of MG. In this proposed controller, particle swarm optimization (PSO) and grey wolf optimization (GWO) are used to optimize the membership functions (MFs) and rule base of fuzzy logic based PI controller. The proposed controller is examined on an MG test system, the robustness and performance of the proposed controller is tested in presence of different disturbance scenarios and parametric uncertainties. Finally, the superiority of the proposed controller is shown by comparing the results with various controllers available in literature like PSO tuned fuzzy logic based PI controller, fuzzy logic-based PI controller and also with the conventional PI controller.     

基于滑模模糊方法的变速风电系统的最大风能捕捉控制器设计

针对具有不确定参数和强干扰的变速风力发电系统,提出一种积分滑模模糊自适应控制器。该控制策略基于带积分补偿的滑模控制器,并利用自适应模糊控制方法,把滑模控制器中的不确定项进行模糊逼近,同时对其中的切换项也进行模糊自适应逼近,从而有效降低变结构控制固有的抖振现象。利用李亚普诺夫函数证明了控制器的稳定性。采用此控制策略,对变速风力发电系统的风轮转速进行跟踪控制,仿真结果显示此控制方法具有较强的鲁棒性和良好的跟踪性能。     

Robust 2DOF fuzzy gain scheduling control for DC servo speed controller

This paper proposes a new design method called “robust 2DOF fuzzy gain scheduling control” for a DC servo speed control system. The proposed technique utilizes the basic concept of 2DOF robust loop shaping, whose time‐domain specifications are combined during the controller design using a reference model. In addition, the local controllers are fixed‐ structure robust controllers whose structure can be specified as for a simple controller. A fuzzy approach is adopted in both system identification process and global control structure to accomplish an entirely robust system. Although the design of robust control in a fuzzy system is not easy, genetic algorithms (GAs) simplify the control design problem to design the fuzzy controller such that the average stability margin is minimized. Implementation of a DC servo speed control was adopted to investigate the effectiveness of the proposed controller. As seen from the results, the proposed controller has more robust performance and can be adopted in applications with a wide operating range. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.