Stability Criteria for Large－Scale Linear Systems with Structured Uncertainties

The robust stability analysis for large scale linear systems with structured time varying uncertainties is investigated in this paper.By using the scalar Lyapunov functions and the properties of M matrix and nonnegative matrix,stability robustness measures are proposed.The robust stability criteria obtained are applied to derive an algebric criterion which is expressed directly in terms of plant parameters and is shown to be less conservative than the existing ones.A numerical example is given to demonstrate the stability criteria obtained and to compare them with the previous ones.

On delay-dependent robust stability for uncertain neutral systems

The problem of delay-dependent criteria for the robust stability of neutral systems with time-varying structured uncertainties and identi-cal neutral-delay and discrete-delay is concerned. A criterion for nominal systems is presented by taking the relationship between the terms in the Leibniz-Newton formula into account, which is described by some free-weighting matrices. In addition, this criterion is extended to robust stability of the systems with time-varying structured uncertainties. All of the criteria are based on linear matrix inequality such that it is easy to calculate the upper bound of the time-delay and the free-weighting matrices. Numerical examples illustrate the effectiveness and the improvement over the existing results.

Delay-dependent criteria for the robust stability of systems with time-varying delay

The problem of delay-dependent robust stability for systems with time-varying delay has been considered. By using the S-procedure and the Park's inequality in the recent issue, a delay-dependent robust stability criterion which is less conservative than the previous results has been derived for time-delay systems with time-varying structured uncertainties. The same idea has also been easily extended to the systems with nonlinear perturbations. Numerical examples illustrated the effectiveness and the improvement of the proposed approach. Keywords Delay-dependent criteria - Robust stability - Time-varying structured uncertainties - Nonlinear perturbations - Linear matrix inequality This work was supported by the Doctor Subject Foundation of China (No. 2000053303).

A NEW METHOD FOR THE UNCERTAIN RESPONSE ANALYSIS OF STRUCTURES WITH UNCERTAIN PARAMETERS

A computing method for estimating the upper and lower bounds of the response of structures with uncertainties is presented. The uncertain parameters are described by the convex model. A numerical example of the frame structure is given to illustrate the effectiveness of this method.

THE UNCERTAIN EIGENVALUES ANALYSIS OF STRUCTURES WITH UNCERTAIN PARAMETERS

This paper presents a method for estimating the upper and lowerbounds of eigenvalues of structures with uncertainties. The uncertainparameters re described by the convex model. A numerical ex- ample ofthe frame structure is given to illustrate the efficiency of themethod.

SEISMIC RANDOM VIBRATION ANALYSIS OF STOCHASTIC STRUCTURES USING RANDOM FACTOR METHOD

Seismic random vibration analysis of stochastic truss structures is presented. A new method called random factor method is used for dynamic analysis of structures with uncertain parameters, due to variability in their material properties and geometry. Using the random factor method, the natural frequencies and modeshapes of a stochastic structure can be respectively described by the product of two parts, corresponding to the random factors of the structural parameters with uncertainty, and deterministic values of the natural frequencies and modeshapes obtained by conventional finite element analysis. The stochastic truss structure is subjected to stationary or non-stationary random earthquake excitation. Computational expressions for the mean and standard deviation of the mean square displacement and mean square stress are developed by means of the random variable＇s functional moment method and the algebra synthesis method. An antenna and a truss bridge are used as practical engineering examples to illustrate the application of the random factor method in the seismic response analysis of random structures under stationary or non-stationary random earthquake excitation.

Interpretation of residual gravity anomaly caused by simple shaped bodies using very fast simulated annealing global optimization

A very fast simulated annealing（VFSA） global optimization is used to interpret residual gravity anomaly.Since,VFSA optimization yields a large number of best-fitted models in a vast model space;the nature of uncertainty in the interpretation is also examined simultaneously in the present study.The results of VFSA optimization reveal that various parameters show a number of equivalent solutions when shape of the target body is not known and shape factor ＇q＇ is also optimized together with other model parameters.The study reveals that amplitude coefficient k is strongly dependent on shape factor.This shows that there is a multi-model type uncertainty between these two model parameters derived from the analysis of cross-plots.However,the appraised values of shape factor from various VFSA runs clearly indicate whether the subsurface structure is sphere,horizontal or vertical cylinder type structure.Accordingly,the exact shape factor（1.5 for sphere,1.0 for horizontal cylinder and 0.5 for vertical cylinder）is fixed and optimization process is repeated.After fixing the shape factor,analysis of uncertainty and cross-plots shows a well-defined uni-model characteristic.The mean model computed after fixing the shape factor gives the utmost consistent results.Inversion of noise-free and noisy synthetic data as well as field data demonstrates the efficacy of the approach.

Delay-dependent robust stability for neutral systems with mixed discrete-and-neutral delays

This paper focuses on the problem of delay-dependent robust stability of neutral systems with different discrete-and-neutral delays and time-varying structured uncertainties. Some new criteria are presented, in which some free weighting matrices are used to express the relationships between the terms in the Leibniz-Newton formula. The criteria include the information on the size of both neutral-and-discrete delays. It is shown that the present results also include the results for identical discrete-and-neutral delays as special cases. A numerical example illustrates the improvement of the proposed methods over the previous methods and the influences between the discrete and neutral delays.

Model predictive control for constrained uncertain piecewise linear systems

For constrained piecewise linear （PWL） systems, the possible existing model uncertainty will bring the difficulties to the design approaches of model predictive control （MPC） based on mixed integer programming （MIP）. This paper combines the robust method and hybrid method to design the MPC for PWL systems with structured uncertainty. For the proposed approach, as the system model is known at current time, a free control move is optimized to be the current control input. Meanwhile, the MPC controller uses a sequence of feedback control laws as the future control actions, where each feedback control law in the sequence corresponds to each partitions and the arbitrary switching technique is adopted to tackle all the possible switching. Furthermore, to reduce the online computational burden of MPC, the segmented design procedure is suggested by utilizing the characteristics of the proposed approach. Then, an offline design algorithm is proposed, and the reserved degree of freedom can be online used to optimize the control input with lower computational burden.

Convergence and error bounds of adaptive filtering under model structure and regressor uncertainties

Adaptive filtering algorithms are investigated when system models are subject to model structure errors and regressor signal perturbations. System models for practical applications are often approximations of high-order or nonlinear systems, introducing model structure uncertainties. Measurement and actuation errors cause signal perturbations, which in turn lead to uncertainties in regressors of adaptive filtering algorithms. Employing ordinary differential equation （ODE） methodologies, we show that convergence properties and estimation bias can be characterized by certain differential inclusions. Conditions to ensure algorithm convergence and bounds on estimation bias are derived. These findings yield better understanding of the robustness of adaptive algorithms against structural and signal uncertainties.