基于切换的多模型二阶段自适应控制器设计

针对一类具有参数跳变特性的离散时间系统,设计一类基于切换策略的新型多模型二阶段自适应控制器.该控制器首先将系统不确定参数的变化空间划分为多个子空间,在每个空间内建立多个自适应模型.为了克服多模型退化,保持模型的多样性以应对参数跳变,采用带约束的二阶段自适应方法对未知参数进行实时估计,并据此设计相应的子控制器;然后基于切换策略,选取该时刻的最优子控制器作为系统的控制器,从而减小系统暂态误差,提高系统动态性能;最后进行数值仿真研究,仿真结果表明该控制器结合了切换机制和二阶段自适应的优点,在相同模型数量的情况下,能够快速逼近参数跳变以后系统新的工作点,显著地缩短系统的过渡过程,提高暂态性能.     

基于不同加权因子的随机多模型自适应控制

针对一类噪声方差未知的随机系统,基于不同加权因子设计多个参数辨识器辨识模型参数,在此基础上,构成多模型自适应控制器.在每个采样时刻基于指标切换函数选择最佳辨识模型.并将基于此最佳模型设计的控制器切换为当前控制器.同时,证明了多个模型控制器之间相互切换时整个闭环系统是全局收敛的.仿真结果表明,同单一自适应模型控制器相比,这种基于多个不同加权因子的多模型自适应控制器在模型参数发生跳变时可很好地改善被控对象的控制品质.     

基于不同加权因子的随机多模型自适应控制

针对一类噪声方差未知的随机系统,基于不同加权因子设计多个参数辨识器辨识模型参数,在此基础上,构成多模型自适应控制器.在每个采样时刻基于指标切换函数选择最佳辨识模型,并将基于此最佳模型设计的控制器切换为当前控制器. 同时,证明了多个模型控制器之间相互切换时整个闭环系统是全局收敛的 .仿真结果表明,同单一自适应模型控制器相比,这种基于多个不同加权因子的多模型自适应控制器在模型参数发生跳变时可很好地改善被控对象的控制品质.

     

一类离散时间非线性系统的多模型自适应控制

针对一类离散时间非线性被控对象,根据模型参数的变化范围,对被控对象建立多个模型,并针对每一模型设计控制器.基于模型的估计误差建立指标切换函数,每一采样时刻,利用指标切换函数选择最优模型,并将基于此模型的控制器切换为当前控制器.采用局部化技术,保证在不损失控制品质的同时,减少多模型自适应控制器的计算量.可以证明,多控制器相互切换时闭环系统是稳定的,同时由于多个模型的存在,控制品质得到了极大的改善.     

基于小波分解的非线性系统多模型自适应控制

提出了一种改进的基于小波分解的非线性系统辨识算法,利用小波函数的逼近能力在线辨识被控对象的非线性项.针对基于小波分解的辨识算法缺乏预测能力,提出了根据线性鲁棒自适应控制器提供的当前控制信息预测未来的非线性项值新方法,并结合多模型方法,根据所定义的切换指标自动切换到当前最优控制器.仿真结果表明,改进的基于小波分解的辨识算法能够有效逼近非线性系统,基于小波分解的非线性系统多模型自适应控制方法改善了系统性能,随着系统运行跟踪误差明显减小,说明了该方法的有效性和可行性.     

基于多模型切换的多变量直接自适应极点配置控制器

提出一种基于多模型切换的多变量直接自适应控制器,控制器参数模型集可由系统参数模型集直接得到,不但仍为一紧集并且被其模型子集完全覆盖.该多模型控制器不仅改善了控制系统的暂态响应,而且可以实现极点配置,最后给出了全局收敛性分析.     

一类工业运行过程多模型自适应控制方法

针对一类动态未知的工业运行过程,提出一种基于神经网络补偿和多模型切换的自适应控制方法.为充分考虑底层跟踪误差对整个运行过程优化和控制的影响,将底层极点配置控制系统和上层运行层动态模型相结合,作为运行过程动态模型.针对参数未知的运行过程动态模型,设计由线性鲁棒自适应控制器、基于神经网络补偿的非线性自适应控制器以及切换机制组成的多模型自适应控制算法.采用带死区的递推最小二乘算法在线辨识控制器参数,克服了投影算法收敛速度慢、对参数初值灵敏的局限.理论分析和仿真实验结果表明了所提方法的有效性.     

一类非最小相位系统的多变量多模型解耦控制器

为解决系统暂态响应变差问题，提出一种基于多模型切换的多变量直接自适应控制器，通过加权多项式矩阵的选择，可消除稳态误差，实现静态解耦控制，该控制器由多个参数已知固定模型和两个自适应模型构成，多个固定参数控制器模型可由系统参数模型通过映射直接得到，并与邻城一起完全覆盖控制器参数模型集，仿真结果表明，对于非最小相位系统，暂态响应可得到明显改善。     

多模型混合H∞型鲁棒控制

基于多模型控制器设计方法中需要建立大量离线子模型,导致计算负担过大的问题,本文提出基于H_∞理论的多模型混合鲁棒控制器设计方法.该方法首先对参数变化区间进行分解,根据得到的子区间建立子模型,从而获得多模型集.然后依据理论设计子模型鲁棒控制器,具有良好的抗干扰性,并能有效地减少子模型数量;其次,针对各鲁棒控制器,设计混合信号实现混合输出,可以很好地解决切换多模型控制中存在的持续切换问题.最后,对本文所提方法进行仿真和聚合釜温度系统的应用研究,结果表明当被控对象参数存在不确定性和存在输入扰动的时候,该方法可以在较少子模型数量的前提下保证系统具有良好的鲁棒性.     

一类时变系统的多模型切换动态调节控制算法

当被控对象参数所在的不确定区域未知时, 多模型切换调节等控制算法虽然最终可以使系统达到期望特 性, 但随着不确定区域的增大, 系统需要增加大量的模型才能满足快速性等方面上的要求. 因此, 为了实现一类时 变系统在只增加少量模型时便能够满足期望控制性能的目标, 提出了多模型切换动态调节控制算法. 此算法在不 确定区域内分配若干上层模型, 在双切换机制的监督下, 利用动态分配方法, 在最优上层模型所在的子区域分配出 若干下层模型, 在与自适应模型的协作中, 设计最优控制器, 保证了系统的暂态和稳态响应. 在数值仿真与故障卫星 系统的仿真研究中, 结果表明了多模型切换动态调节算法在暂态性能方面优于多模型切换调节算法, 并验证了此算 法的有效性.     

Fault diagnosis and accommodation of nonlinear systems based on multiple-model adaptive unscented Kalman filter and switched MPC and H-infinity loop-shaping controller

In this paper, a new active fault tolerant control (AFTC) methodology is proposed based on a state estimation scheme for fault detection and identification (FDI) to deal with the potential problems due to possible fault scenarios. A bank of adaptive unscented Kalman filters (AUKFs) is used as a core of FDI module. The AUKF approach alleviates the inflexibility of the conventional UKF due to constant covariance set up, leading to probable divergence. A fuzzy-based decision making (FDM) algorithm is introduced to diagnose sensor and/or actuator faults. The proposed FDI approach is utilized to recursively correct the measurement vector and the model used for both state estimation and output prediction in a model predictive control (MPC) formulation. Robustness of the proposed FTC system, H_∞ optimal robust controller and MPC are combined via a fuzzy switch that is used for switching between MPC and robust controller such that FTC system is able to maintain the offset free behavior in the face of abrupt changes in model parameters and unmeasured disturbances. This methodology is applied on benchmark three-tank system; the proposed FTC approach facilitates recovery of the closed loop performance after the faults have been isolated leading to an offset free behavior in the presence of sensor/actuator faults that can be either abrupt or drift change in biases. Analysis of the simulation results reveals that the proposed approach provides an effective method for treating faults (biases/drifts in sensors/actuators, changes in model parameters and unmeasured disturbances) under the unified framework of robust fault tolerant control.     

Application of gap metric to model bank determination in multilinear model approach

This paper presents a gap metric based method which aims to perform the operating range decomposition and the minimum linear model bank determination of a nonlinear system when multilinear model approach is employed to design a controller for this nonlinear system. For a prescribed distance level, the minimum linear model bank determined by the proposed method can provide sufficient information for multilinear model controller design of the nonlinear system. To illustrate the usefulness of the proposed method, two examples of nonlinear systems are presented. Moreover, a mixed logical dynamical model-based MPC (MLD–MPC) controller is designed based on the minimum model bank. Simulations confirm the method for selecting linear model bank in multilinear model approach.     

Impact of wind farms on disturbance detection and classification in distributed generation using modified Adaline network and an adaptive neuro-fuzzy information system

A new disturbance detection and classification technique based on modified Adaline and adaptive neuro-fuzzy information system (ANFIS) is proposed for a distributed generation system comprising a wind power generating system (DFIG) and a photovoltaic array. The proposed technique is based on a fast Gauss–Newton parameter updating rule rather than the conventional Widrow–Hoff delta rule for the Adaline network. The voltage and current signals near the target distributed generation (DG), particularly the DFIG, whose speed varies from minimum to the maximum cut-off speed, are processed through the modified Adaline network to yield the features like the negative sequence power, harmonic amplification factor (HAF), total harmonic distortion (THD), etc. These features are then used as training sets for the ANFIS, which employs a gradient descent algorithm to update its parameters. The proposed technique distinguishes the islanding condition of the distributed generation system with some other disturbances, such as switching faults, capacitor bank switching, voltage swell, voltage sag, distorted grid voltage, unbalanced load switching, etc. which are referred to as non-islanding cases in this paper.     

三相电压源型PWM逆变器相电流重构策略研究

基于直流电流、开关状态及三相电流之间的关系，提出用直流电流和开关状态重构逆变器相电流的新方法．歼关状态由改进型电流滞环数字控制器产生．为减小测量噪声和重构相电流误差，设计了IIR（Infinite Impulse Response）数字滤波器．以感应电机矢量控制系统为例进行了仿真研究，结果表明新方法是有效的、准确的．该方法仅需一个直流电流传感器，降低了电机驱动系统成本，提高了系统的容错能力．该方法与电机模型参数及负载变化无关，适用于所有三相平衡电流的交流电机驱动系统．     

有源电力滤波器切换跟踪与优化控制

为了提高有源电力滤波器的动态性能, 基于切换系统理论研究其电流跟踪控制问题. 首先, 建立系统的切换动态模型, 根据切换系统理论和空间电压矢量法证明二次稳定性, 并设计相应的切换控制序列. 考虑到控制器的数字化实现, 建立系统的离散切换系统模型, 提出在采样周期内使系统性能最优的切换控制策略. 仿真结果表明, 该控制策略能实现对指令电流的精确跟踪, 降低功率器件的开关频率, 从而有效地提高系统的动态性能.

     

非线性系统的多模型DMC解耦设计

针对工业生产过程大多为多输入多输出非线性系统,干扰因素多,耦合作用强,常规控制方法难以获得满意控制效果的特.提出一种基于动态矩阵控制(DMC)的多模型控制方法,采用误差指标切换函数作为切换准则,根据其最小值来选择与实际最接近模型,并将基于此模型的控制器切换为当前控制器.结合目标函数解耦方法,在模型中考虑其他通道输入对当...     

遗传算法和神经网络融合的滑模控制系统及其在印刷机中的应用

针对一类非线性系统, 提出了一种综合集成滑模控制器设计方法. 首先, 采用遗传算法进行参数调节, 从而构造出一个最佳切换函数, 使得系统既具有良好的动态性能, 又扩大了鲁棒区域. 然后, 采用神经网络在线调整控制器参数, 从而克服了由不确定性引起的系统轨迹偏离切换函数, 并且通过变学习率学习算法来加快神经网络的收敛性. 最后, 研究了所提出方法在凹版印刷机张力调节中的应用. 仿真结果表明该控制器具有较好的动态性能及鲁棒性, 并有效减少了抖动.     

Fault detection and isolation for uncertain closed‐loop systems based on adaptive and switching approaches

This paper deals with the fault detection and isolation (FDI) problem for uncertain closed‐loop systems with external disturbances and nonlinear perturbations. To address the system uncertainties and the nonlinear perturbations in different faulty models, adaptive and switching techniques are introduced to construct a bank of FDI observers, such that one of them can match the current system, and the corresponding observer estimate errors can converge asymptotically to zero. An effective FDI scheme is then presented by introducing some model‐matching indexes. Moreover, the introduced switching laws liberate the equality constraints often used in the existing FDI approaches, which are hard to satisfy if the system matrices include uncertainties. Finally, a simulation example of F/A‐18A automatic carrier landing system is used to illustrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

基于遗传算法的切换控制器设计与优化

利用遗传算法研究了一类切换规则只由状态决定的切换系统的控制器优化设计问题.首先由线性矩阵不等式(LMI)来设计切换控制器,然后应用遗传算法来对切换规则进行优化.优化后的切换规则不仅可保证闭环系统渐近稳定,而且具有良好的动态性能.将本文提出的方法应用在小车倒立摆控制系统上,仿真结果表明了本文设计方法的有效性.