On design of quantized fault detection filters with randomly occurring nonlinearities and mixed time-delays

This paper is concerned with the fault detection problem for a class of discrete-time systems with randomly occurring nonlinearities, mixed stochastic time-delays as well as measurement quantizations. The nonlinearities are assumed to occur in a random way. The mixed time-delays comprise both the multiple discrete time-delays and the infinite distributed delays that occur in a random way as well. A sequence of stochastic variables is introduced to govern the random occurrences of the nonlinearities, discrete time-delays and distributed time-delays, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fault detection filter such that, in the presence of measurement quantization, the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fault detection filters, and then the explicit expression of the desired filter gains is derived by means of the feasibility of certain matrix inequalities. Also, the optimal performance index for the addressed fault detection problem can be obtained by solving an auxiliary convex optimization problem. A practical example is provided to show the usefulness and effectiveness of the proposed design method

H

This paper investigates the problem of H∞ filtering for class discrete-time Lipschitz nonlinear singular systems with measurement quantization. Assume that the system measurement output is quantized by a static, memoryless, and logarithmic quantizer before it is transmitted to the filter, while the quantizer errors can be treated as sector-bound uncertainties. The attention of this paper is focused on the design of a nonlinear quantized H∞ filter to mitigate quantization effects and ensure that the filtering error system is admissible (asymptotically stable, regular, and causal), while having a unique solution with a prescribed H∞ noise attenuation level. By introducing some slack variables and using the Lyapunov stability theory, some sufficient conditions for the existence of the nonlinear quantized H∞ filter are expressed in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effectiveness of the proposed quantized filter design method

Delay-Dependent H

This paper deals with the problem of delay-dependent H∞ filtering for singular time-delay systems. First, a new delay-dependent condition which guarantees that the filter error system has a prescribed H∞ performance γ is given in terms of linear matrix inequalities (LMIs). Then, the sufficient condition is obtained for the existence of the H∞ filter, and the explicit expression for the desired H∞ filter is presented by using LMIs and the cone complementarity linearization iterative algorithm. A numerical example is provided to illustrate the effectiveness of the proposed method

On Less Conservative Stability Criteria for Neural Networks with Time-Varying Delays Utilizing Wirtinger-Based Integral Inequality

This paper investigates the problem of stability analysis for neural networks with time-varying delays. By utilizing the Wirtinger-based integral inequality and constructing a suitable augmented Lyapunov-Krasovskii functional, two less conservative delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). Three numerical examples are included to explain the superiority of the proposed methods by comparing maximum delay bounds with the recent results published in other literature

Robust filtering of linear time invariant systems by means of polynomial Lyapunov functions

Orientadores: Pedro Luis Dias Peres, Ricardo Coração de Leão Fontoura de OliveiraDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Este trabalho apresenta novas condições na forma de desigualdades matriciais lineares para a síntese de filtros robustos H2 e H¥ de ordem completa, para sistemas incertos, contínuos e discretos no tempo. Os parâmetros incertos invariantes no tempo pertencem a um politopo com vértices conhecidos. Graças à existência de um número maior de variáveis de folga e à utilização de relaxações baseadas em matrizes polinomiais homogêneas, desigualdades matriciais lineares podem ser obtidas das condições propostas para o projeto de filtros robustos, com desempenho superior aos métodos existentes. A superioridade e eficiência do método proposto para o projeto dos filtros robustos são ilustradas por meio de comparações numéricas e exemplos da literaturaAbstract: This work presents new convex optimization procedures for full order robust H2 and H? filter design for continuous and discrete-time uncertain linear systems. The time-invariant uncertain parameters are supposed to belong to a polytope with known vertices. Thanks to the use of a larger number of slack variables and homogeneous polynomial relaxations, linear matrix inequalities for the design of robust filters can be derived from the proposed conditions, outperforming the existingmethods. The superiority and efficiency of the proposed method for robust filter design are illustrated by means of numerical comparisons in benchmark examples from the literatureMestradoAutomaçãoMestre em Engenharia Elétric