基于回路成形的鲁棒增益调度控制器设计

针对目前基于线性变参数系统的增益调度控制设计中存在的控制结构复杂性问题，提出一种基于回路成形的简单且易实现的增益调度控制结构.在此基础上，提出一个鲁棒增益调度控制设计方法.设计过程首先采用补偿器函数使得被控对象奇异值具有期望的形状，以保证被控对象的性能要求，然后利用小增益定理设计一个鲁棒控制器，得到具有良好性能的、结构简单的鲁棒增益调度控制器.最后针对一个化工过程，说明此方法的有效性.     

大包络飞行BTT导弹多模鲁棒控制方法研究

在导弹飞行控制器优化设计的研究中,针对大包络飞行BTT导弹全局H∞鲁棒控制器的设计问题,为了提高系统的稳定性和抗干扰性,将多模型自适应控制方法与传统的控制器增益调度方法相结合,提出一种适合于BTT导弹H∞鲁棒控制器的增益调度方法.针对各子工作区离线设计满足要求的常值参数鲁棒控制器,飞行过程中通过实测的调度参数对各鲁棒控制器输出进行平滑切换,避免引起的参数误差,消减了高阶H∞鲁棒全局控制器参数脆弱性问题的影响.实现对大包络飞行BTT空空导弹姿态稳定性控制,并通过数字仿真验证了方法的有效性.     

高超声速飞行器非线性鲁棒控制律设计

高超声速飞行器具有模型非线性程度高、耦合程度强、参数不确定性大、抗干扰能力弱等特点,其自主控制具有较大的挑战.论文提出了一种基于鲁棒补偿技术和反馈线性化方法的非线性鲁棒控制方法.文中首先采用反馈线性化的方法对纵向模型进行输入输出线性化,实现速度和高度通道的解耦和非线性模型的线性化.针对得到的线性模型,设计包括标称控制器和鲁棒补偿器的线性控制器.基于极点配置原理,设计标称控制器使标称线性系统具有期望的输入输出特性,利用鲁棒补偿器来抑制参数不确定性和外界扰动对于闭环控制系统的影响.基于小增益定理,证明了闭环控制系统的鲁棒稳定性和鲁棒跟踪性能.相比于非线性回路成形控制方法,仿真结果表明了所设计非线性鲁棒控制算法的有效性和优越性.     

基于参数摄动模型的航空发动机鲁棒弹性自适应控制

航空发动机特性随飞行条件和工作状态变化,在复杂工作环境中同时存在模型不确定性和控制器自身参数变化问题,很大程度上影响整个飞行包线的控制性能。为此,文章提出一种基于参数摄动模型的航空发动机鲁棒弹性自适应控制方法。其首先建立了航空发动机参数摄动结构化模型;然后针对被控对象模型的不确定性和控制器增益的摄动,利用李雅普诺夫稳定性（Lyapunov stability）理论和线性矩阵不等式约束,设计了增益摄动有界但上界未知时的鲁棒弹性自适应控制律,将控制器的设计问题转化为线性矩阵不等式的可行解问题,使控制器的设计仅依赖线性矩阵不等式解矩阵的存在性,并证明了算法的稳定性。在此基础上,文章对飞行包线内发动机不同工作状态进行控制仿真验证。结果显示,调节时间小于1.8 s,超调量小于5%,这表明所设计控制器具有良好的稳定性和控制性能。     

机器人LFT变增益H∞控制

针对平面两关节直接驱动机器人,基于LMI技术提出一种设计能保证在整个运动范围内始终具有很好动态性能的LFT变增益H∞控制器的新方法.将机器人系统转化为以两关节夹角余弦值为变参数的LPV模型并表示为关于变参数的LFT结构,利用变参数的测量值设计具有相同LFT结构的LPVH∞控制器,将此控制器的设计等价为以变参数为不确定项的LTI鲁棒控制器的设计并给出控制器可解的LMIs条件,然后归纳出获得控制器的求解方法.此控制器既克服了传统变增益控制器的缺陷,又利用变参数的测量值降低了控制器设计的保守性.实验结果验证了此控制器的有效性和先进性.     

机器人LFT变增益∞控制

针对平面两关节直接驱动机器人, 基于LMI技术提出一种设计能保证在整个运动范围内始终具有很好动态性能的LFT变增益H_∞ 控制器的新方法. 将机器人系统转化为以两关节夹角余弦值为变参数的LPV模型并表示为关于变参数的LFT结构, 利用变参数的测量值设计具有相同LFT结构的LPVH_∞ 控制器, 将此控制器的设计等价为以变参数为不确定项的LTI鲁棒控制器的设计并给出控制器可解的LMIs条件, 然后归纳出获得控制器的求解方法. 此控制器既克服了传统变增益控制器的缺陷,     

空空导弹增益调度鲁棒H_∞控制自动驾驶仪设计

为了满足空空导弹大空域、高机动飞行的技术指标要求,提出了BTT导弹的增益调度鲁棒H∞自动驾驶仪设计方法;建立了BTT导弹线性变参数(LPV)系统数学模型;提出了LPV系统增益调度鲁棒H∞控制设计方法和设计过程;通过把BTT导弹自动驾驶仪分为俯仰、偏航/滚转通道分别进行设计,并以俯仰通道为例进行了仿真验证;仿真结果表明该控制算法具有良好的控制性能,从而,验证了增益调度鲁棒H∞控制算法的正确性和有效性。     

具有输入时滞的不确定采样系统的鲁棒控制北大核心CSCD

针对具有输入时滞的结构不确定采样系统,研究了该类系统基于离散化模型的鲁棒控制器设计问题。通过将采样系统的连续的结构不确定对象离散化得到其近似模型,使具有输入时滞不确定采样系统的鲁棒控制器设计问题转换为讨论具有输入时滞的离散系统的鲁棒稳定性问题。利用Lyapunov函数的构造及解析技巧,给出了基于线性矩阵不等式(LMI)的输入时滞离散系统的鲁棒稳定性条件,并在此基础上将控制器参数化,得到了一个通过求解线性矩阵不等式(LMI)来获得采样系统鲁棒控制器的设计方法,所设计的控制器保证了系统的鲁棒稳定性,对结构摄动有着较好的鲁棒性能。最后,通过数值计算仿真验证了本文方法的可行性。     

具有输入时滞的不确定采样系统的鲁棒控制

针对具有输入时滞的结构不确定采样系统,研究了该类系统基于离散化模型的鲁棒控制器设计问题。通过将采样系统的连续的结构不确定对象离散化得到其近似模型,使具有输入时滞不确定采样系统的鲁棒控制器设计问题转换为讨论具有输入时滞的离散系统的鲁棒稳定性问题。利用Lyapunov函数的构造及解析技巧,给出了基于线性矩阵不等式(LMI)的输入时滞离散系统的鲁棒稳定性条件,并在此基础上将控制器参数化,得到了一个通过求解线性矩阵不等式(LMI)来获得采样系统鲁棒控制器的设计方法,所设计的控制器保证了系统的鲁棒稳定性,对结构摄动有着较好的鲁棒性能。最后,通过数值计算仿真验证了本文方法的可行性。     

不确定离散系统的鲁棒非脆弱H∞控制

针对线性不确定离散系统,研究了鲁棒非脆弱H∞状态反馈控制器的设计问题。鲁棒性是研究被控系统模型参数摄动对闭环系统的影响,脆弱性是研究控制器参数摄动对闭环系统的影响。在系统模型和控制器同时存在不确定时,只有鲁棒非脆弱的控制器才能保证闭环系统的稳定和满足给定性能。系统的不确定项参数时变且具有线性分式形式的范数有界,控制器的增益变化也是时变且具有线性分式形式的范数有界。基于线性矩阵不等式方法,给出了具有加性和乘性控制器增益变化的鲁棒非脆弱控制器存在的充要条件。实例表明了该设计方法的有效性。     

Gain-Scheduling of Minimax Optimal State-Feedback Controllers for Uncertain LPV Systems

A new robust control gain-scheduling scheme for uncertain linear parameter-varying (LPV) systems is proposed. The gain-scheduled controller consists of a set of minimax optimal robust controllers and incorporates a new interpolation rule to achieve continuity of the controller gain over a range of operating conditions. For every fixed system parameter, the proposed controller guarantees a certain bound on the worst-case performance of the corresponding uncertain closed loop system. Furthermore, a bound on the rate of parameter variations is obtained under which the closed loop LPV system is robustly stable     

Low-complexity linear parameter-varying modeling and control of a robotic manipulator

In this paper, a practical procedure for linear parameter-varying (LPV) modeling and identification of a robotic manipulator is presented, which leads to a successful experimental implementation of an LPV gain-scheduled controller. A nonlinear dynamic model of a two-degrees-of-freedom manipulator containing all important terms is obtained and unknown parameters which are required to construct an LPV model are identified. An important tool for obtaining a model of complexity low enough to be suitable for controller synthesis is the principle-component-analysis-based technique of parameter set mapping. Since the resulting quasi-LPV model has a large number of affine scheduling parameters and a large overbounding, parameter set mapping is used to reduce conservatism and complexity in controller design by finding tighter parameter regions with fewer scheduling parameters. A sufficient a posteriori condition is derived to assess the stability of the resulting closed-loop system. To evaluate the applicability and efficiency of the approximated model, a polytopic LPV gain-scheduled controller is synthesized and implemented experimentally on an industrial robot for a trajectory tracking task. The experimental results illustrate that the designed LPV controller outperforms an independent joint PD controller in terms of tracking performance and achieves a slightly better accuracy than a model-based inverse dynamics controller, while having a simpler structure. Moreover, it is shown that the LPV controller is more robust against dynamic parameter uncertainty.     

Fuzzy multi-objective design for a lateral missile autopilot

Gain scheduled control is one very useful control technique for linear parameter-varying (LPV) and nonlinear systems. A disadvantage of gain-scheduled control is that it is not easy to design a controller that guarantees the global stability of the closed-loop system over the entire operating range from the theoretical point of view. Another disadvantage is that the interpolation increases in complexity as number of scheduling parameters increases. As an improvement, this paper presents a gain-scheduling control technique, in which fuzzy logic is used to construct a model representing a quasi-LPV or a nonlinear missile and to perform a control law. The fuzzy inference system is generated using a multi-objective evolutionary algorithm to optimize the performance characteristics of the plant.     

A design of gain-scheduled control for a linear parameter varying system: an application to flight control

For multi-input–multi-output, multi-parameter, nonlinearly parameter-dependent linear parameter-varying systems, a gain-scheduled control design method using both minimum sensitivity eigenvalue assignment and quadratic stability check is proposed. The designed controller guarantees the stability of the closed-loop system and assigns the eigenvalues of the frozen parameter closed-loop LPV system in the prespecified disjointed regions. Fewer controllers than that of any other method are needed to cover the whole parameter space. The proposed design method is applied to the design of a flight vehicle's back-to-turn (BTT) controller and nonlinear six-degree-of-freedom (6-DOF) simulations are performed to show its usefulness as a gain-scheduled controller design method.     

Anti-windup controller design using linear parameter-varying control methods

In this paper, we seek to provide a systematic anti-windup control synthesis approach for systems with actuator saturation within a linear parameter-varying (LPV) design framework. The closed-loop induced L2 gain control problem is considered. Different from conventional two-step anti-windup design approaches, the proposed scheme directly utilizes saturation indicator parameters to schedule accordingly the parameter-varying controller. Hence, the synthesis conditions are formulated in terms of linear matrix inequalities (LMIs) that can be solved very efficiently. The resulting gain-scheduled controller is non-linear in general and would lead to graceful performance degradation in the presence of actuator saturation non-linearities and linear performance recovery. An aircraft longitudinal dynamics control problem with two input saturation non-linearities is used to demonstrate the effectiveness of the proposed LPV anti-windup scheme.     

Gain-scheduled L-one control for linear parameter-varying systems with parameter-dependent delays

This paper deals with the problem of gain-scheduled L-one control for linear parameter-varying (LPV) systems with parameter-dependent delays. The attention is focused on the design of a gain-scheduled L-one controller that guarantees being an asymptotically stable closed-loop system and satisfying peak-to-peak performance constraints for LPV systems with respect to all amplitude-bounded input signals. In particular, concentrating on the delay-dependent case, we utilize parameter-dependent Lyapunov functions (PDLF) to establish peak-to-peak performance criteria for the first time where there exists a coupling between a Lyapunov function matrix and system matrices. By introducing a slack matrix, the decoupling for the parameter-dependent time-delay LPV system is realized. In this way, the sufficient conditions for the existence of a gain-scheduled L-one controller are proposed in terms of the Lyapunov stability theory and the linear matrix inequality (LMI) method. Based on approximate basis function and the gridding technique, the corresponding controller design is cast into a feasible solution problem of the finite parameter linear matrix inequalities. A numerical example is given to show the effectiveness of the proposed approach.     

Simultaneous design of robust gain-scheduled static output-feedback controller and scaling matrices for linear parameter varying systems with inexact scheduling parameters

This article presents a design method of the robust gain-scheduled static output-feedback controller exploiting inexact measured scheduling parameters for multi-affine linear parameter-varying systems with structured uncertainty blocks. Performance scaling matrices are introduced in the design process to reduce conservatism. By introducing auxiliary variables and properly utilizing projection lemma, a parameter-dependent linear matrix inequality with a single line search parameter is derived to synthesize the static output-feedback controller gains and scaling matrices simultaneously. Based on vertices of the convex polytope covering the admissible region of scheduling parameters and inexact ones, the given parameter-dependent synthesis condition is further expressed as a set of linear matrix inequalities at the vertices of the polytope to guarantee the robustness against inaccurate scheduling parameters. Several examples show the effectiveness of the proposed algorithm.     

Filter design for LPV systems using quadratically parameter-dependent Lyapunov functions

This paper considers design problems of robust gain-scheduled H_∞ and H₂ filters for linear parameter-varying (LPV) systems whose state-space matrices are represented as parametrically affine matrices, using quadratically parameter-dependent Lyapunov functions, and proposes methods of filter design via parametrically affine linear matrix inequalities (LMIs). For robust filters, our design methods theoretically encompass those that use constant Lyapunov functions. Several numerical examples are included that demonstrate the effectiveness of gain-scheduled and robust filters using our proposed methods compared with robust filters using existing methods.     

Design of robust gain-scheduled PI controllers for nonlinear processes

Gain-scheduling has proven to be a successful design methodology in many engineering applications. However, in the absence of a sound theoretical analysis, these designs come with no guarantees of robust stability, performance or even nominal stability of the overall gain-scheduled deign.This paper presents such an analysis for one type of nonlinear gain-scheduled control system based on the process input for nonlinear chemical processes. A methodology is also proposed for the design and optimization of the robust gain-scheduled PI controller. Conditions which guarantee robust stability and performance are formulated as a finite set of linear matrix inequalities (LMIs) and hence, the resulting problem is numerically tractable. Issues of modeling error and input-saturation are explicitly incorporated into the analysis. A simulation study of a nonlinear continuous stirred tank reactor (CSTR) process indicates that this approach can produce efficient sub-optimal robust gain-scheduled controllers.     

Inverse system design for LPV systems using parameter-dependent Lyapunov functions

This paper addresses the design problem of gain-scheduled inverse systems (GSISs) for linear parameter-varying (LPV) systems, whose state-space matrices are represented as parametrically affine matrices, using parameter-dependent Lyapunov functions (PDLFs), and proposes a method for them via parametrically affine linear matrix inequalities (LMIs). Our method includes robust inverse system (RIS) design as a special case. For RIS design, our method theoretically encompasses the method using constant Lyapunov functions. A design example is included to illustrate our conclusions.