New robust delay-dependent stability and H∞ analysis for uncertain Markovian jump systems with time-varying delays

This paper deals with the problems of robust delay-dependent stability and H_∞ analysis for Markovian jump linear systems with norm-bounded parameter uncertainties and time-varying delays. In terms of linear matrix inequalities, an improved delay-range-dependent stability condition for Markovian jump systems is proposed by constructing a novel Lyapunov-Krasovskii functional with the idea of partitioning the time delay, and a sufficient condition is derived from the H_∞ performance. Numerical examples are provided to demonstrate efficiency and reduced conservatism of the results in this paper.     

H∞ guaranteed cost control for uncertain Markovian jump systems with mode-dependent distributed delays and input delays

This paper investigates the H_∞ guaranteed cost control problem for mode-dependent time-delay jump systems with norm-bounded uncertain parameters. Both distributed delays and input delays appear in the system model. Based on a matrix inequality, a sufficient condition for the existence of robust H_∞ guaranteed cost controller is derived, which stabilizes the considered system and guarantees that both the H_∞ performance level and a cost function have upper bounds for all admissible uncertainties. By the cone complementary linearization approach, the desired state-feedback controller can be constructed. A numerical example is provided to show the effectiveness of the proposed theoretical results.     

H∞ filtering for nonlinear systems via neural networks

A novel H_∞ filter design methodology has been presented for a general class of nonlinear systems. Different from existing nonlinear filtering design, the nonlinearities are approximated using neural networks, and then are modeled based on linear difference inclusions, which makes the structure of the desired filter simpler and parameter turning easier and has the advantages of guaranteed stability, numeral robustness, bounded estimation accuracy. A unified framework is established to solve the addressed H_∞ filtering problem by exploiting linear matrix inequality (LMI) approach. A numerical example shows that the filtering error systems will work well against bounded error between a nonlinear dynamical system and a multilayer neural network.     

H∞ filtering for linear neutral systems with mixed time-varying delays and nonlinear perturbations

In this paper, the problem of H_∞ filtering for neutral systems with mixed time-varying delays and nonlinear perturbations is investigated. Some new delay-dependent sufficient conditions are presented to ensure that the filtering error system is asymptotically stable with a prescribed level of H_∞ noise attenuation. In addition, the design procedures for the existence of such filter are presented in terms of a set of linear matrix inequalities (LMIs). Slack variables and convex combination technique are adopted to reduce the conservatism of obtained results. Finally, three numerical examples are given to illustrate the effectiveness of the proposed method.     

Nonlinear H∞ robust control applied to F-16 aircraft with mass uncertainty using control surface inverse algorithm

In this paper, an analytic solution of nonlinear H_∞ robust controller is first proposed and used in a complete six degree-of-freedom nonlinear equations of motion of flight vehicle system with mass and moment inertia uncertainties. A special Lyapunov function with mass and moment inertia uncertainties is considered to solve the associated Hamilton-Jacobi partial differential inequality (HJPDI). The HJPDI is solved analytically, resulting in a nonlinear H_∞ robust controller with simple proportional feedback structure. Next, the control surface inverse algorithm (CSIA) is introduced to determine the angles of control surface deflection from the nonlinear H_∞ control command. The ranges of prefilter and loss ratio that guarantee stability and robustness of nonlinear H_∞ flight control system implemented by CSIA are derived. Real aerodynamic data, engine data and actuator system of F-16 aircraft are carried out in numerical simulations to verify the proposed scheme. The results show that the responses still keep good convergence for large initial perturbation and the robust stability with mass and moment inertia uncertainties in the permissible ranges of the prefilter and loss ratio for which this design guarantees stability give same conclusion.     

Dynamical robust H∞ filtering for nonlinear uncertain systems: An LMI approach

In this paper, a new approach to robust H_∞ filtering for a class of nonlinear systems with time-varying uncertainties is proposed in the LMI framework based on a general dynamical observer structure. The nonlinearities under consideration are assumed to satisfy local Lipschitz conditions and appear in both state and measured output equations. The admissible Lipschitz constants of the nonlinear functions are maximized through LMI optimization. The resulting H_∞ observer guarantees asymptotic stability of the estimation error dynamics with prespecified disturbance attenuation level and is robust against time-varying parametric uncertainties as well as Lipschitz nonlinear additive uncertainty.     

H2 and H∞ optimal model reduction using genetic algorithms

The mathematical modeling of most physical systems, such as aerospace systems, heat processes, telecommunication systems, transmission lines and chemical reactors, results in complex high order models. The complexity of the models imposes a lot of difficulties in analysis, simulation and control designs. Several analytical model reduction techniques have been proposed in literature over the past few decades to reduce these difficulties. However, most of the optimal techniques follow computationally demanding, time consuming, iterative procedures that usually result in non-robustly stable models with poor frequency response resemblance to the original high order model in some frequency ranges. Genetic Algorithm (GA) has proved to be an excellent optimization tool in the past few years. Therefore, the aim of this paper will be to use GA to solve H₂ and H_∞ norm model reduction problems, and help obtain globally optimized nominal models.     

Non-fragile robust H∞ control for uncertain discrete-time singular systems with time-varying delays

In this paper, the problem of delay-dependent non-fragile robust H∞$H\infty$ control for a class of discrete-time singular systems with state-delay and parameter uncertainties is investigated. Based on singular value decomposition approach, a delay-dependent sufficient condition for the H∞$H\infty$ control problem for a class of discrete-time singular systems is proposed by constructing generalized Lyapunov–Krasovskii function and a new difference inequality. A memoryless state feedback controller under controller gain perturbations is designed, which guarantees that, for all admissible uncertainties, the resultant closed-loop system is regular, causal, and stable with an H∞$H\infty$ norm bound constraint. Numerical examples in the last will show that our results have the better performance in conservativeness than some results reported in the literature.     

A delay-derivative-dependent approach to robust H∞ filter design for uncertain systems with time-varying distributed delays

This paper focuses on the problem of robust H∞ filter design for uncertain systems with time-varying state and distributed delays. System uncertainties are considered as norm-bounded time-varying parametric uncertainties. The delays are assumed to be time-varying delays being differentiable uniformly bounded with delay-derivative bounded by a constant, which may be greater than one. A new delay-derivative-dependent approach of filter design for the systems is proposed. A novel Lyapunov-Krasovskii functional (LKF) is employed, and a tighter upper bound of its derivative is obtained by employing an inequality and using free-weighting matrices technique, then the proposed result has advantages over some existing results, in that it has less conservatism and it enlarges the application scope. An improved sufficient condition for the existence of such a filter is established in terms of linear matrix inequality (LMI). Finally, illustrative examples are given to show the effectiveness and reduced conservatism of the proposed method.     

Design of mixed H2-dissipative observers with stochastic resilience for discrete-time nonlinear systems

A linear matrix inequality based mixed H₂-dissipative type state observer design approach is presented for smooth discrete time nonlinear systems with finite energy disturbances. This observer is designed to maintain H₂ type estimation error performance together with either H_∞ or a passivity type disturbance reduction performance in case of randomly varying perturbations in its gain. A linear matrix inequality is used at each time instant to find the time-varying gain of the observer. Simulation studies are included to explore the performance in comparison to the extended Kalman filter and a previously proposed constant gain observer counterpart.     

A switched system approach to H∞ control of networked control systems with time-varying delays

This paper is concerned with the H_∞ control problem for a class of networked control systems (NCSs) with time-varying delay that is less than one sampling period. By applying a new working mode of the actuator and considering state feedback controllers, a new discrete-time switched system model is proposed to describe the NCS. Based on the obtained switched system model, a sufficient condition is derived for the closed-loop NCS to be exponentially stable and ensure a prescribed H_∞ performance level. The obtained condition establishes relations among the delay length, the delay variation frequency, and the system performances of the closed-loop NCS. Moreover, a convex optimization problem is formulated to design the H_∞ controllers which minimize the H_∞ performance level. An illustrative example is given to show the effectiveness of the proposed results.     

Delay-dependent H∞ filtering of uncertain Markovian jump delay systems via delay-partitioning approach

In this paper, the problem of _H∞$H_{\infty }$ filtering of uncertain time-delay systems with Markovian jumping parameters is considered. Firstly, by utilizing the delay-partitioning idea, an augmented mode-dependent Lyapunov functional is employed to analyze the stochastic stability and _H∞$H_{\infty }$ performance of the resulting filtering error systems. It is noted that the derived performance analysis results are less conservative than the recent ones in the literature. Secondly, based on the criteria obtained, a desired filter can be constructed by introducing a given nonsingular matrix and a scalar. Numerical examples are given to illustrate the effectiveness of the proposed approach.     

A Markovian system approach to distributed H∞ filtering for sensor networks with stochastic sampling

This paper is concerned with the distributed H_∞ filtering problem for a class of sensor networks with stochastic sampling. System measurements are collected through a sensor network stochastically and the phenomena such as random measurement missing and quantization are also considered. Firstly, the stochastic sampling process of the sensor network is modeled as a discrete-time Markovian system. Then, the logarithmic quantization effect is transformed into the parameter uncertainty of the filtering system, and a set of binary variables is introduced to model the random measurement missing phenomenon. Finally, the resulting augmented system is modeled as an uncertain Markovian system with multiple random variables. Based on the Lyapunov stability theory and the stochastic system analysis method, a sufficient condition is obtained such that the augmented system is stochastically stable and achieves an average H_∞ performance level γ; the design procedure of the optimal distributed filter is also provided. A numerical example is given to demonstrate the effectiveness of the proposed results.     

H∞ control for network-based systems with time-varying delay and packet disordering

The H_∞ control problem is investigated in this paper for a class of networked control systems (NCS) with time-varying delay and packet disordering. A new model is proposed to describe the packet disordering phenomenon and then converted into a parameter-uncertain system with multi-step delay. Based on the obtained system model, a sufficient condition for robust stability of the NCS is derived. Furthermore, an optimization problem with linear matrix inequalities (LMIs) constraints is formulated to design the state feedback H_∞ controller such that the closed-loop NCS is robust stable and has an optimal H_∞ disturbance attenuation level. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed method.     

Central suboptimal H∞ filtering for nonlinear polynomial systems with multiplicative noise

This paper presents the central finite-dimensional H_∞ filter for nonlinear polynomial systems with multiplicative noise, that is suboptimal for a given threshold γ with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the previously obtained results, the paper reduces the original H_∞ filtering problem to the corresponding optimal H₂ filtering problem, using the technique proposed in [1]. The paper presents the central suboptimal H_∞ filter for the general case of nonlinear polynomial systems with multiplicative noise, based on the optimal H₂ filter given in [31]. The central suboptimal H_∞ filter is also derived in a closed finite-dimensional form for third (and less) degree polynomial system states. Numerical simulations are conducted to verify performance of the designed central suboptimal filter for nonlinear polynomial systems against the central suboptimal H_∞ filters available for polynomial systems with state-independent noise and the corresponding linearized system.     

H∞ output-feedback control with randomly occurring distributed delays and nonlinearities subject to sensor saturations and channel fadings

This paper is concerned with the _H∞$H_{\infty }$ output-feedback control problem for a class of discrete-time systems with randomly occurring nonlinearities (RONs) as well as randomly occurring distributed delays (RODDs). Both RONs and RODDs are governed by random variables obeying the Bernoulli distributions. The measurement output is subject to the sensor saturations described by sector-nonlinearities as well as the channel fadings caused typically in wireless communication. The aim of the addressed problem is to design a full-order dynamic output-feedback controller such that, in the simultaneous presence of RONs, RODDs, sensor saturations and channel fadings, the closed-loop system is exponentially mean-square stable and satisfies the prescribed _H∞$H_{\infty }$ performance constraint. By using a combination of the stochastic analysis and Lyapunov functional approaches, sufficient conditions are derived for the existence of the desired controllers and then the characterization of such controllers is given via the semi-definite programme method. Finally, the numerical simulation result is exploited to illustrate the usefulness and effectiveness of the proposed design technique.     

Robust fault detection for a class of nonlinear time-delay systems

In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. Firstly, a reference residual model is introduced to formulate the robust fault detection filter design problem as an H_∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H_∞ optimization control technique, the existence conditions of the robust fault detection filter for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.     

Delay-dependent stochastic stability and H∞ analysis for time-delay systems with Markovian jumping parameters

This paper studies the problem of the stochastic stability and H_∞ disturbance attenuation for linear continuous-time time-delay systems that possess randomly Markovian jumping parameters. A delay-dependent sufficient condition on the stochastic stability with given H_∞ performance is proposed using the stochastic Lyapunov–Krasovskii stability theory. The conditions are formulated as a set of coupled linear matrix inequalities.     

Nonlinear H∞ feedback control with integrator for polynomial discrete-time systems

This paper investigates the problem of designing a nonlinear _H∞$H_{\infty }$ feedback controller for polynomial discrete-time systems with and without polytopic uncertainties. The objective is to design a controller such that the ratio between the energy of the regulated outputs and the energy of the exogenous disturbance/inputs is minimized or guaranteed to be less or equal to a prescribed value. It is well known that the state dependant or parameter dependant Lyapunov function is always chosen for synthesizing polynomial discrete-time systems. This leads the solution to be nonconvex because the Lyapunov function and the controller matrix are coupled and therefore cannot be solved by semidefinite programming (SDP). Hence, in this paper, an integrator is proposed to be incorporated into the controller structure. In doing so, the coupling of Lyapunov function and controller matrix can be eliminated effectively. This somehow simplifies the numerical solution of the problem. Then, by using SOS decomposition approach, sufficient conditions for the existence of the proposed controller are provided in terms of solvability of the state-dependent linear matrix inequalities (SDLMIs) which can be solved by SDP. A tunnel diode circuit is used to demonstrate the effectiveness of this integrator approach.     

Non-fragile H∞ filter design with sparse structure for linear discrete-time systems

This paper presents a study on the problem of designing non-fragile _H∞$H_{\infty }$ filters with sparse structure for linear discrete-time systems. The filters to be designed with sparse structure are assumed to be with additive gain variations, which are resulted from filter implementations. Firstly, a class of sparse structures is specified from a given fully parameterized _H∞$H_{\infty }$ filter. Then, an LMI-based procedure for designing non-fragile _H∞$H_{\infty }$ filters with the sparse structure is provided. The resulting design guarantees the augmented system asymptotically stable and the _H∞$H_{\infty }$ attenuation level less than a prescribed level. A numerical example is given to illustrate the proposed method.