不确定模糊Delta算子系统的鲁棒H∞控制

研究了一类T-S模糊Delta算子系统的鲁棒H_∞控制问题.首先利用LMI形式给出了模糊Delta算子系统鲁棒镇定的充分条件,然后构造了可使闭环系统鲁棒稳定且对可允许的参数变化满足H_∞性能的状态反馈控制律.本文结果统一了连续与离散模糊系统的鲁棒H_∞镇定设计结论,数值算例说明了方法的可行性.     

不确定脉冲系统的鲁棒H∞控制

首次提出并研究了不确定脉冲系统的鲁棒H_∞控制问题. 基于代数Riccati方程正定矩阵解的存在性, 建立了不确定脉冲闭环系统具有鲁棒H_∞特性的充分性准则, 同时给出了相应的状态反馈控制设计方法, 并用数值例子说明了所得结果的有效性.     

一类不确定非线性系统的鲁棒H∞控制

在一种工程应用背景之下, 考虑了一类非线性系统的鲁棒H_∞ 控制问题, 不确定性范数有界, 基于HJI不等式研究了状态反馈控制器设计问题, 使得闭环系统满足H_∞ 干扰抑制性能要求.     

基于Kp=S1D1U1分解的多变量鲁棒模型参考自适应控制

针对具有噪声的多变量系统,利用高频增益矩阵K。_p=S_1D_1U_1分解,提出了一种多变量鲁棒直接型模型参考自适应控制．通过重新证明一些同单变量系统鲁棒自适应控制理论相似的性质,及重新定义规范化信号,找出了闭环系统的所有信号与规范化信号之间的关系,严格地分析了闭环系统的稳定性和鲁棒性．     

基于博弈论的H2/H∞混合控制及其在汽车主动悬架中的应用

文章提出把H₂/H_∞混合控制问题抽象为两个对局者信息不完全情况下的非零和博弈模型.在构造2×2非零和博弈模型中把反映系统鲁棒性能通道和动态性能通道作为参加博弈的两方,以H_∞和H₂控制方案作为两种纯策略,基于纳什谈判解原理设计出求解H₂/H_∞混合控制问题纳什均衡点的一般算法.把该算法应用于汽车主动悬架设计出基于纳什均衡点的H₂/H_∞输出反馈控制器.使用MATLAB进行仿真,仿真结果表明主动悬架系统在保持鲁棒稳定性与获得优化的动态性能指标之间取得平衡.     

MIMO离散时间系统混合l1/H2控制

研究了MIMO(多输入多输出)离散时间系统的混合l₁/H₂优化问题,该问题可描述为最优化一个传递函数矩阵的l₁范数同时保证另一个传递函数矩阵的H₂范数满足预定的指标.研究了最优目标函数值关于H₂范数指标的连续性.证明了MIMO系统混合l₁/H₂控制问题最优解的存在性.由于基于标定-Q(scaled-Q)方法求解MIMO混合l₁/H₂问题,避免了进行零点插值运算的困难.通过求解有限维非线性规划问题可得到最优目标值的收敛的上下界.     

具有非线性扰动的广义系统的鲁棒H∞控制

研究具有非线性结构扰动广义系统的鲁棒H_∞控制和鲁棒H_∞保性能控制问题,该不确定性为时间和状态的函数,且满足Lipschitz条件.目的是分别设计系统的鲁棒H_∞控制器和鲁棒H_∞保性能控制器.应用线性矩阵不等式方法,分别给出了系统的鲁棒H_∞控制器和鲁棒H_∞保性能控制器存在的充分条件.当这些条件可解时,分别给出了鲁棒H_∞控制器和鲁棒H_∞保性能控制器的表达式.最后通过一个仿真算例说明了所给出方法的应用.

     

混合H2/H∞参数辨识

研究了混合H₂/H_∞参数辨识问题.将混合H₂/H_∞估计方法应用到系统参数辨识中,给出了混合H₂/H_∞参数辨识算法.所得的算法不仅能满足规定的鲁棒性能,且为最小二乘(LS)参数估计误差判据提供了一个最优上界.结果表明:提高辨识的鲁棒性,需要牺牲辨识的精度作为代价.最后,仿真结果也验证了该方法的有效性.     

不确定Delta算子系统的鲁棒H∞重构控制

讨论一类含有参数不确定和执行器故障的Delta算子系统鲁棒H_∞ 重构控制设计问题. 通过利用故障检测与隔离(FDI)技术, 在考虑不可检测故障执行器输入为能量有界的干扰信号情形下, 基于H_∞ 干扰抑制的思想, 给出了系统可鲁棒H_∞ 镇定的充分条件. 所设计的控制器可使闭环系统鲁棒稳定, 而且对可允许的不确定性和执行器故障具有一定的H_∞ 性能. 数值例子说明了本文设计方法的有效性.     

一种可保证瞬态特性的改进的鲁棒模型参考自适应控制

针对典型的鲁棒模型参考自适应控制中瞬态性能无法得到保障的问题, 提出一种改进的鲁棒模型参考自适应控制器. 该控制器在标准的鲁棒自适应控制中加入??_∞ 补偿器, 以抑制闭环自适应系统中参数估计误差和不确定扰动对系统输出跟踪性能造成的不利影响. 理论分析和仿真验证表明, 所提出的控制器不但保留了典型鲁棒模型参考自适应控制的理想特性, 并且通过设计适当的??∞ 补偿器使得闭环系统的瞬态性得到了较大的改善, 其改善的程度依赖于??∞ 补偿器性能指标的大小.

     

Stability and robustness analysis of MIMO MRAC using Kp = L 2 D 2 S 2 factorization

For a class of MIMO systems with input and output unmodeled dynamics, bounded disturbances and any relative degree, using the idea of K_p = L ₂ D ₂ S ₂ factorization, the design and analysis of robust direct model reference adaptive control are further investigated in this article. By establishing the L_p and L _2δ relationship properties between the input and output, multivariable swapping lemmas and relating all the signals in the closed-loop system with the normalizing signal, stability and robustness of adaptive system are analyzed rigorously. Compared with the existing results, the proof procedure is more compact and simple. A simulation example verifies the effectiveness of the control scheme.     

Robust direct model reference adaptive control using KP = LDU factorization for multivariable plants

Motivated by the idea of high frequency gain matrix K_P ?=?LDU factorization, the purpose of this paper is to study the problem of robust direct model reference adaptive control for more general multivariable plants with unmodeled dynamics and disturbances. For multivariable plants, by reproving some properties similar to those in robust adaptive control theory for SISO plants and redefining the normalizing signal, the relationship between all the signals in the closed-loop plant and the normalizing signal can be established, and the stability and robustness of the closed-loop plant are analyzed rigorously from a qualitative point of view.     

四旋翼无人机L1 自适应块控反步姿态控制器设计

针对四旋翼无人机的姿态控制问题,提出一种L1自适应块控反步控制方法.将四旋翼姿态运动模型转化为一类多输入多输出不确定非线性系统的形式;根据该系统严格反馈的结构特点,对外回路设计了块控反步控制器;针对内回路存在的外部干扰和内部参数摄动等不确定性,引入L1自适应控制思想补偿其影响.稳定性分析表明闭环系统内所有信号一致有界.仿真和姿态稳定实验验证了所提控制策略的有效性和鲁棒性.     

Nonlinear robust H∞ control via dynamic output feedback

The problem on robust H_∞ control for a class of nonlinear systems with parameter uncertainty is studied. Sufficient conditions for the existence of the dynamic output feedback controller are obtained. Under these conditions, the closed-loop systems have robust H_∞-performance. A numerical example is given to illustrate the design of a robust controller using the proposed approach.     

A new approach to robust and non-fragile H∞ control for uncertain fuzzy systems

This paper investigates the robust H_∞ control and non-fragile control problems for Takagi-Sugeno (T-S) fuzzy systems with linear fractional parametric uncertainties. The robust H_∞ control problem is to design a state feedback controller such that the robust stability and a prescribed H_∞ performance of the resulting closed-loop system is ensured. And the non-fragile H_∞ control problem is to design a state feedback controller with parameter uncertainties. Based on the linear matrix inequality (LMI) approach, new sufficient conditions for the solvability of the two problems are obtained. It is shown that the desired state feedback fuzzy controller can be constructed by solving a set of LMIs. Numerical examples are also provided to demonstrate the effectiveness of the proposed design method.     

Robust H∞ control for uncertain discrete-time systems with circular pole constraints

This paper investigates the problem of robust H_∞ control for uncertain discrete-time systems with circular pole constraints. The system under consideration is subject to norm-bounded time-invariant uncertainties in both the state and input matrices. The problem we address is to design state feedback controllers such that the closed poles are located within a prespecified circular region, and the H_∞ norm of the closed-loop transfer function is strictly less than a given positive scalar for all admissible uncertainties. By introducing the notion of quadratic d stabilizability with an H_∞ norm-bound, the problem is solved. Necessary and sufficient conditions for quadratic d stabilizability with an H_∞ norm-bound are derived. Our results can be regarded as extensions of existing results on robust H_∞ control and robust pole assignment of uncertain systems.     

Convergent algorithms for frequency weighted L2 model reduction

This paper is concerned with computing an L₂-optimal reduced-order model for a given stable multivariable linear system in the presence of input and output frequency weightings. By parametrizing a class of reduced-order models in terms of an orthogonal projection and using manifold techniques as tools, both continuous and iterative algorithms are derived and their convergence properties are established. As an application, we show that an L₂ optimal reduced-order filter in the closed-loop sense can be computed using these algorithms.     

H∞ Controller design for spectral MIMO models by convex optimization

A new method for robust fixed-order H_∞ controller design by convex optimization for multivariable systems is investigated. Linear Time-Invariant Multi-Input Multi-Output (LTI-MIMO) systems represented by a set of complex values in the frequency domain are considered. It is shown that the Generalized Nyquist Stability criterion can be approximated by a set of convex constraints with respect to the parameters of a multivariable linearly parameterized controller in the Nyquist diagram. The diagonal elements of the controller are tuned to satisfy the desired performances, while simultaneously, the off-diagonal elements are designed to decouple the system. Multimodel uncertainty can be directly considered in the proposed approach by increasing the number of constraints. The simulation examples illustrate the effectiveness of the proposed approach.