线性分式扰动下奇异系统鲁棒滤波递推算法

研究了线性分式扰动下线性奇异系统的状态估计问题, 给出了一种 Kalman 形式的递推滤波算法. 研究表明, 线性分式不确定性可以表示为一系列加性不确定性的交集. 本文讨论了如何寻找保守性最弱的加性不确定性来近似该交集, 并证明了该问题在鲁棒滤波过程中可以转化为凸优化问题. 数值仿真验证了上述算法的有效性. 对于具有结构约束的线性分式不确定性, 该算法的性能优于现有算法.     

Robust estimation for discrete time‐varying systems with limited communication capacity

In this paper, we consider the state estimation problem for linear discrete time‐varying systems subject to limited communication capacity which includes measurement quantization, random transmission delay and data‐packet dropouts. Based on transforming the three communication limitations into the system with norm‐bounded uncertainties and stochastic matrices, we design a robust filter such that, for all the communication limitations, the error state of the filtering process is mean square bounded. An upper bound on the variance of the state estimation error is first found, and then, a robust filter is derived by minimizing the prescribed upper bound in the sense of the matrix norm. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati‐like difference equations which also provide a recursive algorithm suitable for online computation. A simulation example is presented to demonstrate the effectiveness and applicability of the proposed algorithm. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Robust state estimator design for uncertain linear systems using optimization techniques

The estimation of state variables of dynamic systems in noisy environments has been an active research field in recent decades. In this way, Kalman filtering approach may not be robust in the presence of modeling uncertainties. So, several methods have been proposed to design robust estimators for the systems with uncertain parameters. In this paper, an optimized filter is proposed for this problem considering an uncertain discrete-time linear system. After converting the subject to an optimization problem, three algorithms are used for optimizing the state estimator parameters: particle swarm optimization (PSO) algorithm, modified genetic algorithm (MGA) and learning automata (LA). Experimental results show that, in comparison with the standard Kalman filter and some related researches, using the proposed optimization methods results in robust performance in the presence of uncertainties. However, MGA-based estimation method shows better performance in the range of uncertain parameter than other optimization methods.     

多丢包不确定离散系统的鲁棒Kalman滤波

研究了同时具有不确定性和多丢包情况下的离散时变系统的鲁棒滤波问题, 其中的不确定性是时变的、范数有界的, 且存在于系统的状态矩阵和输出矩阵中. 通过把多丢包问题建模成系统模型中的随机参数, 在允许的不确定性情况下, 给出了估计误差方差的上界, 并进一步基于矩阵范数的意义最小化该上界. 结果表明, 通过求解两个Riccati差分方程, 可以设计鲁棒滤波器. 最后, 提出适合在线计算的鲁棒滤波算法, 并通过仿真实例表明所提算法的有效性和实用性.     

奇异线性随机跳变系统有界误差估计器设计

从随机稳定的基本定义开始,对奇异线性随机跳变系统的随机稳定问题进行分析,推导出满足鲁棒∞性能的随机稳定条件,并在此基础上进行推广.首先针对估计误差满足鲁棒∞性能约束的条件,给出带Kalman滤波器形式的滤波器设计方法;然后重点研究了系统中各模态参数矩阵带有不确定性的情况;最后给出相应的数值算例并计算滤波器系数,验证了该方法的有效性和正确性.     

Robust passivity and feedback passification of a class of uncertain fractional-order linear systems

Theoretical results on robust passivity and feedback passification of a class of uncertain fractional-order (FO) linear systems are presented in the paper. The system under consideration is subject to time-varying norm-bounded parameter uncertainties in both the state and controlled output matrices. Firstly, some suitable notions of passivity and dissipativity for FO systems are proposed, and the relationship between passivity and stability is obtained. Then, a sufficient condition in the form of linear matrix inequality (LMI) for such system to be robustly passive is given. Based on this condition, the design method of state feedback controller is proposed when the states are available. Moreover, by using matrix singular value decomposition and LMI techniques, the existing condition and method of designing a robust observer-based passive controller for such systems are derived. Numerical simulations demonstrate the effectiveness of the theoretical formulation.     

LMI-based robust admissible control for uncertain singular delta operator systems

This paper investigates the problem of state feedback robust admissible control for singular delta operator systems with norm-bounded coefficient matrix uncertainties. A necessary and sufficient condition is derived to ensure the admissibility of the closed-loop singular delta operator system for all allowable uncertainties. Then, by specifying the structure of some matrix variables, the existence condition and explicit expression of a robust admissible controller are obtained in terms of strict linear matrix inequalities. Moreover, from the relation between singular discrete systems and singular delta operator systems, the corresponding results are also presented for uncertain singular discrete systems. Finally, some numerical examples are provided to demonstrate the effectiveness of the results in this paper.     

Robust dichotomy of the Lur'e system with structured uncertainties

This paper is concerned with the problem of robust dichotomy of a Lur'e system with norm constraint structured uncertainties, which represent numerous kinds of uncertainties, including mixed real/complex dynamic uncertainties. Leonov's frequency-domain dichotomy condition for Lur'e systems is generalized to the situation where the linear part of the system includes structured uncertainties. By applying the structured singular value of an operator to structured uncertainty, the results on robust dichotomy analysis of the Lur'e system are obtained. Finally a numerical example is included to demonstrate the validity and the applicability of the proposed approach.     

Robust state estimation for uncertain linear systems with deterministic input signals

In this paper, we investigate state estimations of a dynamical system in which not only process and measurement noise, but also parameter uncertainties and deterministic input signals are involved. The sensitivity penalization based robust state estimation is extended to uncertain linear systems with deterministic input signals and parametric uncertainties which may nonlinearly affect a state-space plant model. The form of the derived robust estimator is similar to that of the well-known Kalman filter with a comparable computational complexity. Under a few weak assumptions, it is proved that though the derived state estimator is biased, the bound of estimation errors is finite and the covariance matrix of estimation errors is bounded. Numerical simulations show that the obtained robust filter has relatively nice estimation performances.     

Robust Fault Detection for Switched Linear Systems With State Delays

This correspondence deals with the problem of robust fault detection for discrete-time switched systems with state delays under an arbitrary switching signal. The fault detection filter is used as the residual generator, in which the filter parameters are dependent on the system mode. Attention is focused on designing the robust fault detection filter such that, for unknown inputs, control inputs, and model uncertainties, the estimation error between the residuals and faults is minimized. The problem of robust fault detection is converted into an H _infin-filtering problem. By a switched Lyapunov functional approach, a sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed method.     

Robust H∞ Filtering For Uncertain Stochastic Time‐Delay Systems

This paper deals with the problem of robust H_∞ filtering for uncertain stochastic systems. The system under consideration is subject to time‐varying norm‐bounded parameter uncertainties and unknown time delays in both the state and measurement equations. The problem we address is the design of a stable filter that ensures the robust stochastic stability and a prescribed H_∞ performance level for the filtering error system irrespective of all admissible uncertainties and time delays. A suffient condition for the solvability of this problem is proposed and a linear matrix inequality approach is developed for the design of the robust H_∞ filters. An illustrative example is provided to demonstrate the effctiveness of the proposed approach.     

Robust H ∞ filtering for discrete time-varying uncertain systems with a known deterministic input

In this paper, a new discrete-time dynamic game where two players seek to reinforce and suppress the output of a system under the influence of a known deterministic input is considered. A necessary and sufficient condition for the existence of a saddle-point solution to this game is derived in terms of a discrete-time Riccati difference equation. The result of the game is used to solve the robust H X filtering problem for discrete time-varying systems subject to a known deterministic input and norm-bounded parameter uncertainties occurring in both the state and the output matrices of the state-space model. There is no restriction on the form of the filter. This allows the effect of the known input on the estimation error due to system uncertainties to be optimally reduced without any prior assumption on the filter structure.     

Stabilization of Non‐Linear Fractional‐Order Uncertain Systems

In this paper, we present a stabilization method on the non‐linear fractional‐order uncertain systems. Firstly, a sufficient condition for the robust asymptotic stabilization of the non‐linear fractional‐order uncertain system is presented based on direct Lyapunov approach. Secondly, utilising the matrix's singular value decomposition (SVD) method, the systematic robust stabilization design algorithm is then proposed. Finally, two numerical examples are provided to illustrate the efficiency and advantage of the proposed algorithm.     

滞后离散广义系统的鲁棒严格耗散控制

研究确定的及不确定的滞后离散广义系统的无记忆状态反馈严格耗散控制器设计问题.利用线性矩阵不等式(LMI)方法,首先给出滞后离散广义系统容许(即正则、稳定、因果)且严格耗散的条件,然后通过矩阵不等式(MIs)得到无记忆状态反馈严格耗散控制器的存在条件和设计方法;进而针对除E外其余系数矩阵均具有范数有界不确定性的滞后离散广义系统,利用矩阵不等式的解设计鲁棒严格耗散控制器,保证闭环系统广义二次稳定且严格耗散.     

Robust Adaptive Fractional‐Order Terminal Sliding Mode Control for Lower‐Limb Exoskeleton

This paper introduces a robust adaptive fractional‐order non‐singular fast terminal sliding mode control (RFO‐TSM) for a lower‐limb exoskeleton system subject to unknown external disturbances and uncertainties. The referred RFO‐TSM is developed in consideration of the advantages of fractional‐order and non‐singular fast terminal sliding mode control (FONTSM): fractional‐order is used to obtain good tracking performance, while the non‐singular fast TSM is employed to achieve fast finite‐time convergence, non‐singularity and reducing chattering phenomenon in control input. In particular, an adaptive scheme is formulated with FONTSM to deal with uncertain dynamics of exoskeleton under unknown external disturbances, which makes the system robust. Moreover, an asymptotical stability analysis of the closed‐loop system is validated by Lyapunov proposition, which guarantees the sliding condition. Lastly, the efficacy of the proposed method is verified through numerical simulations in comparison with advanced and classical methods.     

Robust output consensus for a class of fractional‐order interval multi‐agent systems

This paper is devoted to the robust output consensus problem of fractional‐order interval multi‐agent systems (FOIMASs) with fixed undirected topologies, where the fractional order, the system matrix, and the input matrix are perturbed simultaneously, and there exist linear coupling relationships among the fractional order and the perturbations of the system matrix and the input matrix. According to the information of the agents' neighbors, we design a distributed output feedback protocol. A sufficient condition guaranteeing the robust output consensus of FOIMASs is derived in terms of nonlinear matrix inequalities. By the matrix transformation and the singular value decomposition, the nonlinear matrix inequalities are transformed into linear matrix inequalities, and the output feedback gain matrix is obtained. A numerical simulation example is presented to demonstrate the effectiveness of the proposed method.     

一类不确定Lurie时滞奇异系统的鲁棒H∞控制

研究一类具有不确定性的Lurie时滞奇异系统的鲁棒稳定性分析和H∞状态反馈控 制器设计方法.针对一类具有参数不确定性、未知时滞的奇异系统,得出了系统鲁棒稳定和 鲁棒H∞状态反馈控制器存在的充分条件,它能使得不确定Lurie时滞奇异系统的解在所容 许的范围内是正则的、无摄动的和稳定的;而且还得出了基于线性矩阵不等式(LMI)的鲁棒 H∞状态反馈控制器的设计方法,使得闭环系统具有鲁棒稳定性和H∞性能.     

一类不确定Lurie时滞奇异系统的鲁棒H∞滤波

This paper deals with the problem of the robust H∞ filtering for a class of Lurie singular systems with state time-delays,parameter uncertainties and unknown statistics characteristics but with limited power disturbance, aiming to design a robustly stable filter such that the uncertain Lurie time-delay singular systems are not only regular, impulse free and stable, but also have a prescribed level of H∞ performance for the filtering error dynamics for all admissible uncertainties. A sufficient condition for the existence of such a filter is proposed in terms of linear matrix inequalities (LMIs). When a solution to this set of LMIs exists, the parametric matrices of a desired filter can be easily obtained using LMI toolbox.