Reliable H-infinity filtering for linear systems with sensor saturation

In this paper, a new reliable H-infinity filter design problem is proposed for a class of continuous-time systems with sensor saturation and failures. Attention is focused on the analysis and synthesis problems of a full order reliable H-infinity filter such that the filtering error dynamics is asymptotically stable with a guaranteed disturbance rejection attenuation level γ. It is shown that the filtering error dynamics obtained from the original system plus the filter can be modeled by a linear system with sector bounded nonlinearity. The design conditions are given in terms of solutions to a set of linear matrix inequalities (LMIs). These conditions are then considered in a convex optimization problem with LMIs constraints in order to design an optimal reliable H-infinity filter. A numerical example is given to illustrate the effectiveness of the proposed results.     

基于LMI的一类非线性多时滞系统的模糊H∞滤波器设计

This paper develops fuzzy H1 filter for state estimation approach for nonlinear discrete-time systems with multiple time delays and unknown bounded disturbances. We design a stable fuzzy H1 filter based on the Takagi-Sugeno (T-S) fuzzy model, which assures asymptotic stability and a prescribed H1 index for the filtering error system. Sufficient condition for the existence of such a filter is established by solving the linear matrix inequality (LMI) problem. The LMI problem can be efficiently solved with global convergence using the interior point algorithm. Simulation examples are provided to illustrate the design procedure of the proposed method.     

Fuzzy H_∞ Filter Design for a Class of Nonlinear Systems with Time Delays via LMI

This paper develops fuzzy H_∞filter for state estimation approach for nonlinear discrete- time systems with multiple time delays and unknown bounded disturbances.We design a stable fuzzy H_∞filter based on the Takagi-Sugeno (T-S) fuzzy model,which assures asymptotic stability and a prescribed H_∞index for the filtering error system.Sufficient condition for the existence of such a filter is established by solving the linear matrix inequality (LMI) problem.The LMI problem can be efficiently solved with global convergence using the interior point algorithm.Simulation examples are provided to illustrate the design procedure of the proposed method.     

考虑有限字长影响的离散时间非脆弱H∞滤波

The nonfragile H_∞filtering problem affected by finite word length (FWL) for linear discrete-time systems is investigated in this paper.The filter to be designed is assumed to be with additive gain variations,which reflect the FWL effects on filter implementation.A notion of structured vertex separator is proposed to deal with the problem and exploited to develop sufficient conditions for the nonfragile H_∞filter design in terms of a set of linear matrix inequalities (LMIs).The design renders the augmented system asymptotically stable and guarantees the H_∞attenuation level less than a prescribed level.A numerical example is given to illustrate the effect of the proposed method.     

Stable adaptive fuzzy control of nonlinear systems using small-gain theorem and LMI approach

A new design scheme of stable adaptive fuzzy control for a class of nonlinear systems is proposed in this paper. The T-S fuzzy model is employed to represent the systems. First, the concept of the so-called parallel distributed compensation (PDC) and linear matrix inequality (LMI) approach are employed to design the state feedback controller without considering the error caused by fuzzy modeling. Sufficient conditions with respect to decay rate α are derived in the sense of Lyapunov asymptotic stability. Finally, the error caused by fuzzy modeling is considered and the input-tostate stable (ISS) method is used to design the adaptive compensation term to reduce the effect of the modeling error. By the small-gain theorem, the resulting closed-loop system is proved to be input-to-state stable. Theoretical analysis verifies that the state converges to zero and all signals of the closed-loop systems are bounded. The effectiveness of the proposed controller design methodology is demonstrated through numerical simulation on the chaotic Henon system.     

具有测量数据部分丢失的离散系统的H∞滤波器设计

For packet-based transmission of data over a network, or temporary sensor failure, etc., data samples may be missing in the measured signals. This paper deals with the problem of H∞ filter design for linear discrete-time systems with missing measurements. The missing measurements will happen at any sample time, and the probability of the occurrence of missing data is assumed to be known. The main purpose is to obtain both full-and reduced-order filters such that the filter error systems are exponentially mean-square stable and guarantee a prescribed H∞ performance in terms of linear matrix inequality (LMI). A numerical example is provided to demonstrate the validity of the proposed design approach.     

Distributed \begin{document}$H_{2}/H_\infty$\end{document} Filter Design for Discrete-Time Switched Systems

This paper addresses an infinite horizon distributed H2/H∞ filtering for discrete-time systems under conditions of bounded power and white stochastic signals. The filter algorithm is designed by computing a pair of gains namely the estimator and the coupling. Herein, we implement a filter to estimate unknown parameters such that the closed-loop multi-sensor accomplishes the desired performances of the proposed H2 and H∞ schemes over a finite horizon. A switched strategy is implemented to switch between the states once the operation conditions have changed due to disturbances. It is shown that the stability of the overall filtering-error system with H2/H∞ performance can be established if a piecewise-quadratic Lyapunov function is properly constructed. A simulation example is given to show the effectiveness of the proposed approach.     

H_∞ Filter Design for Discrete-time Systems with Missing Measurements

For packet-based transmission of data over a network, or temporary sensor failure, etc., data samples may be missing in the measured signals. This paper deals with the problem of H∞ filter design for linear discrete-time systems with missing measurements. The missing measurements will happen at any sample time, and the probability of the occurrence of missing data is assumed to be known. The main purpose is to obtain both full-and reduced-order filters such that the filter error systems are exponentially mean-square stable and guarantee a prescribed H∞ performance in terms of linear matrix inequality (LMI). A numerical example is provided to demonstrate the validity of the proposed design approach.     

Observer-Based Adaptive Fuzzy Tracking Control Using Integral Barrier Lyapunov Functionals for A Nonlinear System With Full State Constraints

A new fuzzy adaptive control method is proposed for a class of strict feedback nonlinear systems with immeasurable states and full constraints.The fuzzy logic system is used to design the approximator,which deals with uncertain and continuous functions in the process of backstepping design.The use of an integral barrier Lyapunov function not only ensures that all states are within the bounds of the constraint,but also mixes the states and errors to directly constrain the state,reducing the conservativeness of the constraint satisfaction condition.Considering that the states in most nonlinear systems are immeasurable,a fuzzy adaptive states observer is constructed to estimate the unknown states.Combined with adaptive backstepping technique,an adaptive fuzzy output feedback control method is proposed.The proposed control method ensures that all signals in the closed-loop system are bounded,and that the tracking error converges to a bounded tight set without violating the full state constraint.The simulation results prove the effectiveness of the proposed control scheme.     

线性不确定广义时滞系统的鲁棒无源滤波器设计

研究一类线性不确定广义时滞系统的鲁棒无源滤波器设计问题．系统中所含的不确定性假设是未知且范数有界的．利用线性矩阵不等式方法和Lyapunov函数方法相结合,给出了广义滤波增广系统时滞独立的鲁棒无源滤波器的存在条件．设计目标是对所有的不确定性,滤波增广系统是正则、稳定、无脉冲的,且满足所提的无源滤波性能指标．所提的滤波器设计问题可转化为标准的线性矩阵不等式的求解问题,并可推广到多时滞情况．数值例子验证了设计方法的可行性．     

Weighted‐average ℓ1 filtering for switched positive systems

In this paper, the filtering problem for a class of switched positive systems with dwell time is investigated. A novel weighted‐average technique is proposed for filter design such that the final estimate of the unmeasurable outputs of the considered system is more accurate than that of traditional approaches. The main contributions of this paper are summarized as follows: By exploiting the positivity and characteristics of switched positive systems with dwell time, a candidate linear copositive Lyapunov function, which is both quasi‐time‐dependent and mode‐dependent, is presented to establish the closed‐loop stability of the considered systems. Upon the established closed‐loop stability, less conservative bounded positive filters (both upper‐bound and lower‐bound filter) with ? ₁ disturbance attenuation performance are designed for the considered system. By introducing a proper weight, a weighted‐average approach, which is more general than the bounded filter design method, is proposed for filter design. The worst ? ₁ disturbance attenuation performance of the novel developed filter is evaluated. Both the bounded filters and the weighted‐average filter are designed by solving standard linear programming problems. A numerical example illustrates the effectiveness of the proposed approach. Copyright © 2017 John Wiley & Sons, Ltd.     

State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems

This paper aims to develop state observer-based adaptive fuzzy control techniques for controlling a class of uncertain nonlinear systems with bounded external disturbances. An adaptive fuzzy observer is proposed to estimate the system state variables. It is shown that the observation errors obtained from the observer are uniformly ultimately bounded. Applying the estimated system state for design of an output-feedback controller, the uniformly ultimate boundedness of the tracking errors for the resulting closed-loop system can be guaranteed. A typical robot arm system is employed in our simulation studies, and the results demonstrate the usefulness and effectiveness of the proposed techniques for controlling nonlinear systems with bounded external disturbances.     

Filtering for a class of nonlinear MIMO uncertain time-delay stochastic systems

In this article, a high-gain nonlinear observer-based approach is proposed for filtering of nonlinear stochastic systems with time delays. The system under consideration contains parameter uncertainties, stochastic disturbances, time delays, as well as Lipschitz-like nonlinearities. The objective is to design a robust filter such that the dynamics of the estimation error is guaranteed to be stochastically exponentially ultimately bounded in a sense of mean square. A new high-gain filter idea is introduced to solve the stochastic filtering problem by using the Lyapunov method and stochastic analysis techniques. The design of the proposed filter does not necessitate the resolution of any dynamics systems and its expression is explicitly given, i.e. its calibration is achieved through the choice of a single parameter, and does not rely on solving any matrix inequalities by numerical computation. A simulation example is given to illustrate the performance of the proposed filter.     

Moving-horizon state estimation for nonlinear discrete-time systems: New stability results and approximation schemes

A moving-horizon state estimation problem is addressed for a class of nonlinear discrete-time systems with bounded noises acting on the system and measurement equations. As the statistics of such disturbances and of the initial state are assumed to be unknown, we use a generalized least-squares approach that consists in minimizing a quadratic estimation cost function defined on a recent batch of inputs and outputs according to a sliding-window strategy. For the resulting estimator, the existence of bounding sequences on the estimation error is proved. In the absence of noises, exponential convergence to zero is obtained. Moreover, suboptimal solutions are sought for which a certain error is admitted with respect to the optimal cost value. The approximate solution can be determined either on-line by directly minimizing the cost function or off-line by using a nonlinear parameterized function. Simulation results are presented to show the effectiveness of the proposed approach in comparison with the extended Kalman filter.     

Robust H ∞ filtering for uncertain discrete piecewise time-delay systems

This paper investigates the problem of robust H _∞ filter design for uncertain discrete piecewise time-delay systems based on a piecewise Lyapunov functional. The parametric uncertainties are assumed to be time-varying but norm bounded. The purpose is the design of a piecewise filter such that, for all admissible uncertainties, the resulting filtering error system is asymptotically stable and satisfies a prescribed H _∞ performance level. By introducing some different extra matrix variables, a sufficient condition for the solvability of this problem is obtained in terms of linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of a desired piecewise filter is given. Two numerical examples are provided to demonstrate the effectiveness of the proposed design method.     

Filtering on nonlinear time-delay stochastic systems

In this paper, we address the filtering problem for a general class of nonlinear time-delay stochastic systems. The purpose of this problem is to design a full-order filter such that the dynamics of the estimation error is guaranteed to be stochastically exponentially ultimately bounded in the mean square. Both filter analysis and synthesis problems are considered. Sufficient conditions are proposed for the existence of desired exponential filters, which are expressed in terms of the solutions to algebraic Riccati inequalities involving scalar parameters. The explicit characterization of the desired filters is also derived. A simulation example is given to illustrate the design procedures and performances of the proposed method.     

离散系统的鲁棒卡尔曼滤波新方法

提出了一个线性离散不确定系统的卡尔曼滤波新算法,当系统矩阵和观测矩阵都存在不确定误差时,该算法能保证系统的滤波误差有界。相对不确定系统的标称系统来说,该算法是无偏的。与同类处上比,该算法计算简单,计算量较小,实际算例显示了算法的有效性。     

时滞不确定离散系统的鲁棒l2-l∞滤波

将l2-l∞性能指标引入时滞不确定离散时间系统,研究基于这一指标的滤波器设计问 题.所研究的对象是同时具有状态时滞和多面体不确定性的离散时间系统.采用线性矩阵不等 式技术推导了此类不确定系统鲁棒l2-l∞滤波器存在的充分条件,并将滤波器的设计转化为一 个凸优化的求解问题,可以采用较为有效的内点方法进行求解.所设计的滤波器能够保证相对 于所有能量有界的外界扰动信号,滤波误差系统具有一定的l2-l∞扰动衰减水平.数值仿真验 证了所提出算法的可行性.