To evaluate the fault risk of a small railway turnout ballast clearing machine, this paper employs Analytic Hierarchy Process (AHP) to assess reliability based on subjective experience. Additionally, fuzzy comprehensive evaluation method is utilized quantify risk. This combined approach facilitates construction an objective and rational assessment system for ballast-clearing machine. The four main factors, which include rake claw fault, bearing chain sprocket are analysed using Process,...

In this paper, it is shown that the observer-based robust H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control of a class discrete-time systems with state uncertainties conditioned by solvability linear matrix inequality. We show problem, which originally non-convex issue, can be transformed into convex problems using an particular The new proposed inequality neither iterative nor subject to any equality constraint. A flight system...

In this paper, the problem of fault-tolerant control design for nonlinear system based on adaptive robust observer is presented. The aim research to a controller make stable after fault occurs information that obtained from observer. constitution law given and sufficient condition existence designed derived in form LMI. At last, simulation result shown demonstrate feasibility effectiveness proposed approach.

In this paper, a novel PID feedback control algorithm for nonlinear networked systems with random delays is presented by new performance index. The index represented both maximizing information potential of tracking error and minimizing the square incremental input. estimated Parzen windows quadratic Gaussian kernels. convergence in mean sense has been analysed closed loop stochastic NCSs. Simulation results show effectiveness proposed approach.

In this paper, the problem of delay-dependent robust stability for uncertain neutral stochastic neural networks with time delays is considered. Based on Lyapunov theory combined linear matrix inequalities (LMIs) techniques, some new conditions in terms LMIs are derived by introducing free weighting matrices and using Leibniz-Newton formula which can be selected properly to lead less conservative results. Finally, a numerical example given illustrate feasibility effectiveness

The asymptotic stability in the mean square is studied for a class of discrete-time uncertain stochastic neural networks with Markovian jumping parameters this paper. By introducing some free weighting matrices and constructing right Lyapunov-Krasovskii functional, we get an novel global criteria. Conditions are proposed to guarantee robust via linear matrix inequality approach. Finally, numerical example given illustrate feasibility effectiveness results.

This paper investigates the problem of robust stability for a class uncertain discrete-time stochastic recurrent neural networks (RNNs) with Markovian jumping parameters and mode-dependent delays. Stochastic item is nonlinear, are considered as discrete time, discrete-state Markov process. We can get novel conditions in terms linear matrix inequality (LMI) approach. Furthermore, we will introduce into some free weighting matrices by adding to zero order lead much less conservative results....

In this paper, the problem of stochastic stability for a class time-delay Hopfield neural networks with Markovian jump parameters is investigated. The jumping are modeled as continuous-time, discrete-state Markov process. Without assuming boundedness, monotonicity and differentiability activation functions, result delay-dependent criteria (MJDHNNs) developed. We establish that sufficient conditions can be essentially solved in terms linear matrix inequalities.

In this paper, the problem for recurrent neural networks is considered. It stochastic and contains jumping parameters which are continuous-time Markov process. Delay mode-dependent model affected by multiplicative noise. Based on Lyapunov stability theory combined with linear matrix inequalities (LMIs) techniques, we would get some new criteria to guarantee that they robust stable their L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>...

Objective The grey model [GM (1,1)] and the ARIMA multiple seasonal were used to predict incidence trend of brucellosis in Chengde, effects predictions two models is compared. Methods According statistical results epidemiological research monthly patients Chengde from 2008 2014, we established GM (1,1) model, individually predicted 2015. Compared with actual monitoring results, average relative error was verify reliability model. Results GM 0(k)= 0.001 6 (0+ 23 712.31) exp...