QFT与神经网络并行控制研究

阐述了定量反馈理论(Quantitative Feedback Theory，简称QFT)的基本原理及设计步骤，并给出了设计实例。在QFT的基础上，提出了一种QFT和神经网络并行控制的方案，以QFT为主控制器，神经网络进行动态误差补偿。QFT控制能克服对象的参数不确定性，保障系统的鲁棒性；神经网络可以进一步提高系统的跟踪精度。仿真表明，这种方法实现了QFT控制和神经网络控制的完美结合，很适合高精度伺服系统的鲁棒控制。     

基于灵敏度理论的μ/QFT鲁棒飞行控制器设计

针对具有大的不确定性和非线性特性的对象,研究了一种综合μ方法和定量反馈理论(QFT)的鲁棒控制器的设计方法,使闭环系统具有良好的鲁棒性;该方法在利用μ理论设计初始控制器的基础上,采用QFT方法进行优化整形;其中,为便于μ方法权函数的选择和QFT边界曲线的计算,引进鲁棒控制中的灵敏度设计方法进行分析;最后,通过对一个实例的仿真分析验证了该方法的有效性和可行性。     

一种基于QFT的锅炉水位鲁棒控制及分析

在工业实际应用中,锅炉汽包水位在系统动态特性发生较大变化并且受到各种干扰因素影响时,模型的参数将发生变化,成为一个不确定系统.基于此种情况,本文应用定量反馈理论(QFT),提出了基于QFT的锅炉水位鲁棒控制方案,即内回路采用小积分常数比例积分控制器快速消除给水扰动,外回路应用QFT理论设计出主控制器并对主控制器的PID参数进行了整定,以保证水位无静态偏差,仿真结果表明,此种控制方法能够达到比较满意的效果.     

基于多环QFT的飞行仿真转台鲁棒控制

阐述了定量反馈理论(QFT)的基本原理及设计方法,并给出了某型飞行仿真转台的QFT控制器设计实例。为了有效地抑制高频测量噪声对系统的干扰,以及避免系统的高频不确定性,在单环QFT控制的基础上,引入了基于多环QFT的鲁棒控制。理论分析和仿真实验表明,这种多环QFT控制可以明显地缩减控制器的带宽,使系统具有很强的抗高频测量噪声的性能,达到了理想的控制效果。该方法在转台的控制上取得了成功的应用,具有广泛的应用价值。     

基于QFT和ZPETC的高精度鲁棒跟踪控制器设计

阐述了定量反馈理论(QFT)和零相差跟踪控制器(ZOETC)的基本原理及设计方法,并给出了设计实例。在QFT和ZPETC的基础上,提出了一种是实现高精度鲁棒跟踪控制的方案,采用QFT控制保证系统的鲁棒性,通过ZPETC提高系统的跟踪精度。仿真表明,这种方法实现了QFT和ZPETC的完美结合,很适合高精度跟踪系统的鲁棒控制。     

基于QFT的无人机纵向飞行控制系统设计

介绍了定量反馈理论(QFT)的基本原理和设计步骤;定量反馈理论作为一种新颖的频率域鲁棒控制技术,综合考虑了对象的不确定性范围和系统的性能指标要求,以定量方式进行分析设计,从而保证了设计结果具有稳定鲁棒性和性能鲁棒性;无人机飞行过程中具有较强的不确定性,气动参数会不断发生变化,运用QFT对无人机纵向飞行控制系统进行设计,可以很好解决飞行控制系统中的不确定性问题;仿真结果显示,QFT设计的控制器能够很好地满足无人机鲁棒稳定性指标和跟踪性能,符合纵向控制的要求。     

无人侦察机目标跟踪系统鲁棒控制

在已建立的陀螺稳定平台数学模型的基础上,利用定量反馈理论,设计了无人机目标跟踪系统的鲁棒控制器,并对某型无人机目标跟踪鲁棒控制系统进行了仿真,结果表明:采用QFT鲁棒控制器可以有效地消除干扰影响,较好地实现了高低环与方位环的解耦,较准确地实现了目标跟踪.     

基于定量反馈理论算法的电动执行器控制系统的设计

介绍了的一种带网络通信和遥控调试等功能的新型数字式电动执行器控制系统。针对受控对象模型不确定性和无超调跟踪性能要求，设计了基于定量反馈理论(QFT)的二自由度控制器。硬件凋试和控制算法仿真实验，证明了系统的实际可行性。     

定量反馈理论发展综述

定量反馈理论是一种基于频域的鲁棒控制理论,可以用于具有高度不确定性的单变量线性/非线性系统、多变量线性/非线性系统控制器设计.本文概述了定量反馈理论的基本原理、设计过程以及特点.总结了近年来QFT在提高系统性能、鲁棒稳定性、自动设计以及应用等方面的最新研究进展,并且给出了一些已有的理论应用成果.最后讨论了进一步的研究方向.     

定量反馈理论（QFT）及其设计应用

本文总结了定量反馈理论（QFT）的设计特点 、基本原理和设计过程,综合论述了多输入多输出、非最小相位/不稳定、时变/非线性不确 定系统的QFT研究方法,介绍了QFT目前在国外的研究进展及应用情况,并对QFT未来发展作 了展望．     

融合GPC和QFT对不确定性系统的鲁棒控制

针对广义预测控制(GPC)与定量反馈理论(QFT)的特点,提出了把两种算法融合的鲁棒控制算法。该方法是在对QFT进行修改的基础上,采用双回路控制。内回路采用QFT控制器实现对系统不确定性的控制;外回路采用GPC控制器,实现对系统的各种性能要求并且提高鲁棒性。该方法可以充分利用两种控制理论的优点。最后的仿真结果显示,融合的算法比单独采用其中的任何一种控制算法所取得的控制效果都好。     

Automated synthesis of multivariable QFT controller using interval constraint satisfaction technique

Robust controller synthesis of Multi-Input–Multi-Output (MIMO) systems is of great practical interest and their automation is a key concern in control system design. The synthesis problem consists of obtaining a controller that ensures stability and meets a given set of performance specifications, in spite of the disturbance and model uncertainties. In addition to perform the above tasks, a MIMO controller also has to perform the difficult task of minimizing the interaction between the various control loops.Unlike existing manual or convex optimization based Quantitative Feedback Theory (QFT) design approaches, the proposed method gives a controller which meets all performance requirements in QFT, without going through the conservative and sequential design stages for each of the multivariable sub-systems. In this paper, a new, simple, and reliable automated MIMO QFT controllers design methodology is proposed. A fixed structure MIMO QFT controller has been synthesized by solving QFT quadratic inequalities of robust stability and tracking specifications. The quadratic inequalities (constraints) are posed as Interval Constraint Satisfaction Problem (ICSP). The constraints are solved by constraint solver — RealPaver. The main feature of this method is that the algorithm finds all the solutions to within the user-specified accuracy. The designed MIMO QFT controllers are tested on the experimental setup designed by Educational Control Product (ECP) Magnetic Levitation Setup ECP 730. From the experimental results presented, it is observed that, the designed controller satisfies the desired performance specifications. It is also observed that, the interactions between the loops are within the specified limits. The robustness of the designed controllers are verified by putting extra weights on the magnets.     

Stability of quantitative feedback designs and the existence of robust QFT controllers

Quantitative feedback theory (QFT) has received much criticism for a lack of clearly stated mathematical results to support its claims. Considered in this paper are two important fundamental questions: (i) whether or not a QFT design is robustly stable, and (ii) does a robust stabilizer exist. Both these are precursors for synthesizing controllers for performance robustness. Necessary and sufficient conditions are given to resolve unambiguously the question of robust stability in SISO systems, which in fact confirms that a properly executed QFT design is automatically robustly stable. This Nyquist-type stability result is based on the so-called zero exclusion condition and is applicable to a large class of problems under some simple continuity assumptions. In particular, the class of uncertain plants include those in which there are no right-half plane pole-zero cancellations over all plant uncertainties. A sufficiency condition for a robust stabilizer to exist is derived from the well-known Nevanlinna-Pick theory in classical analysis. Essentially the same condition may be used to answer the question of existence of a QFT controller for the general robust performance problem. These existence results are based on an upper bound on the nominal sensitivity function. Also considered is QFT design for a special class of interval plants in which only the poles and the DC gain are assumed uncertain. The latter problem lends itself to certain explicit computations that considerably simplify the QFT design problem.     

基于INA—QFT的高超声速飞行器鲁棒控制器设计

针对高超声速飞行器数学模型的不确定性,提出基于逆奈氏阵列法设计预补偿器和定量反馈理论设计控制器相结合的方法。该方法首先对相互关联的飞行器三通道进行预补偿,使开环前向通道的逆传递函数矩阵成为对角优势阵。然后根据某型号飞行器俯仰通道多个模型参数变化范围,利用定量反馈理论进行鲁棒控制器设计。线性和非线性仿真结果表明,该方法跟踪效果良好,具有较强的工程应用价值。     

On quantitative feedback design for robust position control of hydraulic actuators

This paper discusses several practical issues related to the design of robust position controllers for hydraulic actuators by quantitative feedback theory (QFT). Important properties of the hydraulic actuator behavior, for control system design, are identified by calculating a family of equivalent frequency responses from acceptable nonlinear input–output data. The role of this modeling approach towards reducing over-design by decreasing the sizes of the QFT plant templates is described. The relationship between the geometry of the QFT bounds and the complexity of the robust feedback law is examined through the development of two low-order controllers having characteristics suitable for different applications. Experimental test results demonstrate the extent that each QFT controller is able to maintain robustness against variations in the hydraulic system dynamics that occur due to changing load conditions as well as uncertainties in the hydraulic supply pressure, valve spool gain, and actuator damping.     

Interactive parameter space design for robust performance of MISO control systems

This paper presents a method for the design of nonconservative low-order controllers achieving robust performance in the case of multi-input single-output parallel structure plants subject to unstructured uncertainty. The first step is the analytical generation of gain-phase controller bounds, as in quantitative feedback theory (QFT). Then, to avoid the difficult step of QFT loop shaping, which often produces high-order controllers, these bounds are translated into the controller parameter space where the iterative design of low fixed order controllers takes place. This, as well as the design transparency offered by this technique, constitutes appreciable advantages over the other popular robust performance design method of /spl mu/-synthesis. Other important features are the fact that no extra conservatism is introduced by the method presented and the fact that the method is directly compatible with a sequential loop closing strategy. Finally, the direct search optimization of any additional secondary criteria is possible.     

Design and validation of linear robust controllers for nonlinear plants

This paper describes a robust nonlinear control system design procedure inspired by the nonlinear control ideas of Horowitz's Quantitative Feedback Theory. The central concept is the identification of a family of linear time-invariant (LTI) plants that is equivalent to an uncertain nonlinear (and/or time varying) plant in the sense that an LTI controller feasible for this linear plant family is also feasible for the original nonlinear plant. We identify two conditions for evaluating an equivalent linear family (the equivalence condition and the continuity condition) and show that when these two conditions are satisfied an LTI controller that provides satisfactory robust control of an equivalent linear plant family also provides satisfactory robust control for the related uncertain nonlinear plant, independent of the robust design technique used. We then use these two conditions to analyse the validity of the nonlinear QFT design technique published earlier. Our results suggest that nonlinear QFT can be an attractive approach to nonlinear robust control but its validity (in the sense that the linear design solves the nonlinear control problem) can be demonstrated only if additional conditions and contraints not previously reported are satisfied. © 1998 John Wiley & Sons, Ltd.     

Robust multiple model adaptive control: Modified using ν‐gap metric

A new robust adaptive control method is proposed, which removes the deficiencies of the classic robust multiple model adaptive control (RMMAC) using benefits of the ν‐gap metric. First, the classic RMMAC design procedure cannot be used for systematic design for unstable plants because it uses the Baram Proximity Measure, which cannot be calculated for open‐loop unstable plants. Next, the %FNARC method which is used as a systematic approach for subdividing the uncertainty set makes the RMMAC structure being always companion with the µ‐synthesis design method. Then in case of two or more uncertain parameters, the model set definition in the classic RMMAC is based on cumbersome ad hoc methods. Several methods based on ν‐gap metric for working out the mentioned problems are presented in this paper. To demonstrate the benefits of the proposed RMMAC method, two benchmark problems subject to unmodeled dynamics, stochastic disturbance input and sensor noise are considered as case studies. The first case‐study is a non‐minimum‐phase (NMP) system, which has an uncertain NMP zero; the second case‐study is a mass‐spring‐dashpot system that has three uncertain real parameters. In the first case‐study, five robust controller design methods (H₂, H_∞, QFT, H_∞ loop‐shaping and µ‐synthesis) are implemented and it is shown via extensive simulations that RMMAC/ν/QFT method improves disturbance‐rejection, when compared with the classic RMMAC. In the second case‐study, two robust controller design methods (QFT and mixed µ‐synthesis) are applied and it is shown that the RMMAC/ν/QFT method improves disturbance‐rejection, when compared with RMMAC/ν/mixed?µ. Copyright © 2010 John Wiley & Sons, Ltd.