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This paper examines the event-triggered filtering problem related to discrete-time nonlinear systems that are described by interval type-2 (IT2) fuzzy models. The filter being studied is prone to a non-stationary Markovian process when both quantization output and deception attack are taken into account simultaneously. It is proposed to implement an asynchronous IT2 fuzzy filter characterized by two different piecewise-stationary Markov chains specifying the deception attacks and the modes of the system. A new event-triggering protocol (ETP) is investigated as a means of reducing unnecessary signal transmissions on the communication channel. Based on the linear matrix inequality analysis and using the information on upper and lower membership functions, it is demonstrated that stochastic sufficient conditions exist for the desired filter such that it exhibits mean square stability and achieves the prescribed mixed H ∞ and passivity performance index. Moreover, an optimization-based problem for computing filter gains is proposed. An experimental numerical illustration based on a truck-trailer system is used to validate the developed scheme. [ABSTRACT FROM AUTHOR]

In this work, a new finite element (FE) EDM model was established to estimate the material removal rate (MRR) and thermal stresses in the AISI 316L and AISI D2 steels. Numerical simulation of EDM process was performed using dynamic coupled thermo-mechanical analysis considering plane-strain assumption. Different thermal loading conditions were tested during numerical simulation of the discharge phase while altering heat input size function. Time-dependent plasma channel radius forms with and without discharge current effect have been investigated for each material. The appropriate discharge radius function was identified for each grade of steel based on the comparison of numerically predicted MRR-discharge current diagrams with experiments from previously published work. It was found that the heat input size functions that take into account the effect of discharge current are the most suitable for the prediction of the MRR. Moreover, thermal stresses were predicted via a cooling analysis. The confrontation between experiment and the computed thermal stress profiles for the AISI 316L in the same erosion regime was deemed satisfactory. [ABSTRACT FROM AUTHOR]

The accurate model of the solar PV system is the principal organ that describes the performance of this resource. Several approaches based on optimizing algorithms were considered valuable tools to illustrate the I–V curve for improving the photovoltaic models. Their electrical parameters are estimated using optimization algorithms referring to the experimental database or manufacturer's datasheet. This paper proposes a novel developed a photovoltaic model based on improved arithmetic optimization algorithm (IAOA) to extract the solar cell parameters. Also, an experimental test bench is presented for obtaining the measured illustration of the I–V characteristics. Thus, the root mean square error value that describes the difference between measured and estimated results is considered the objective function for two different models, the simple-diode model and the one-diode model. The proposed IAOA results are compared with other research papers and optimization algorithms. Furthermore, the evaluation of the proposed IAOA has been discussed considering several statistical analysis tests. The presented results show that the effectiveness and accuracy of IAOA results are excellent, and their I–V characteristics coincide with experimental data. Moreover, the results obtained by the proposed algorithm show its high superiority in optimizing the solar cell parameters under a variety of operating conditions. [ABSTRACT FROM AUTHOR]

The present work investigates the Takagi–Sugeno (T–S) fuzzy-based fault-tolerant control for non-linear descriptor systems with uncertainties, external disturbances, and actuator failures. More precisely, the sliding mode control (SMC) approach is employed to develop an observer-based (SMC) strategy for this class of models with the assumption that the sub-model-input matrices can be different. First, an observer is designed to reconstruct the unmeasured states, and a novel integral sliding function, which involves a non-linear term to compensate the matched uncertainty, is formulated. Based on an appropriate fuzzy Lyapunov function, sufficient conditions are established in terms of linear matrix inequality (LMI) to ensure the robust admissibility of the closed-loop system with a satisfactory mixed H ∞ /passivity performance and determine the sliding function parameters. Then, an adaptive observer-based SMC law is synthesized to adaptively ensure the reachability of the sliding surface and completely compensate for the influence of the previously mentioned factors. Finally, the efficiency of the theoretical findings is shown by the implementation of the proposed reliable SMC controller for practical systems about the pendulum and truck-trailer. [ABSTRACT FROM AUTHOR]