Global robust passivity analysis for stochastic fuzzy interval neural networks with time-varying delays

In this paper, the problem of passivity analysis is investigated for uncertain stochastic fuzzy interval neural networks with time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. For the neural networks under study, a generalized activation function is considered, where the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By constructing proper Lyapunov-Krasovskii functional and employing a combination of the free-weighting matrix method and stochastic analysis technique, new delay-dependent passivity conditions are derived in terms of linear matrix inequalities (LMIs), which can be solved by some standard numerical packages. Finally, numerical examples are given to show the effectiveness and merits of the proposed method.     

An Energy-efficient Switching Scheme with Reduced Switching Transients for a Wind-driven Induction Generator

This article presents a scheme for improving the power output of grid-connected induction generator commonly used in wind energy conversion systems. Generally, the stator of the induction generator is connected in a star with a line voltage of √3 times the rated winding voltage to reduce the line current and, hence, conductor size. To extend the generating operation over a wider speed range, delta-star switchable stator windings are also in vogue. In such cases, the stator is star connected in the lower speed range and switched to a delta connection above a threshold speed. In this study, a new switching scheme is proposed wherein the stator coils are always connected in a star, while the stator is connected to different voltages in low- and high-speed conditions. At low wind speeds, nominal winding voltage is applied to the stator, whereas at higher speeds, the stator applied voltage is √3 times higher than the rated winding voltage. The efficacy of the scheme is demonstrated experimentally with a suitable microcontroller-based switching arrangement. Typical results indicate an increase in output with reduced switching transients. A case study on a 3-Φ, 50-kW induction generator is presented to emphasize the performance improvement with the proposed scheme.     

Crack stability in edge-notched clamped beam specimens: modeling and experiments

Stability of a fracture toughness testing geometry is important to determine the crack trajectory and R-curve behavior of the specimen. Few configurations provide for inherent geometric stability, especially when the specimen being tested is brittle. We propose a new geometrical construction called the single edge notched clamped bend specimen (SENCB), a modified form of three point bending, yielding stable cracking under load control. It is shown to be particularly suitable for small-scale structures which cannot be made free-standing, (e.g., thin films, coatings). The SENCB is elastically clamped at the two ends to its parent material. A notch is inserted at the bottom center and loaded in bending, to fracture. Numerical simulations are carried out through extended finite element method to derive the geometrical factor f(a/W) and \(\hbox {K}_{\mathrm{I}}\) for different beam dimensions. Experimental corroborations of the FEM results are carried out on both micro-scale and macro-scale brittle specimens. A plot of \(\hbox {K}_{\mathrm{I}}\) vs a/W, is shown to rise initially and fall off, beyond a critical a/W ratio. The difference between conventional SENB and SENCB is highlighted in terms of \(\hbox {K}_{\mathrm{I}}\) and FEM simulated stress contours across the beam cross-section. The \(\hbox {K}_{\mathrm{IC}}\) ’s of bulk NiAl and Si determined experimentally are shown to match closely with literature values. Crack stability and R-curve effect is demonstrated in a PtNiAl bond coat sample and compared with predicted crack trajectories from the simulations. The stability of SENCB is shown for a critical range of a/W ratios, proving that it can be used to get controlled crack growth even in brittle samples under load control.     

Dissipativity and passivity analysis of Markovian jump impulsive neural networks with time delays

This paper discusses the issue of dissipativity and passivity analysis for a class of impulsive neural networks with both Markovian jump parameters and mixed time delays. The jumping parameters are modelled as a continuous-time discrete-state Markov chain. Based on a multiple integral inequality technique, a novel delay-dependent dissipativity criterion is established via a suitable Lyapunov functional involving the multiple integral terms. The proposed dissipativity and passivity conditions for the impulsive neural networks are represented by means of linear matrix inequalities. Finally, three numerical examples are given to show the effectiveness of the proposed criteria.     

Single-stage sine-wave inverter for an autonomous operation of solar photovoltaic energy conversion system

This paper proposes a high performance single-stage inverter topology for the autonomous operation of a solar photovoltaic system. The proposed configuration which can boost the low voltage of photovoltaic (PV) array, can also convert the solar dc power into high quality ac power for driving autonomous loads without any filter. An MPPT circuit with parallel connection is implemented so that the part of the energy generated is processed by the dc–dc converter to supply dc loads. The line current total harmonic distortion (THD) obtained using this configuration is quite reasonable. The proposed topology has several desirable features such as low cost and compact size as number of switches used, are limited to four as against six switches used in classical two-stage inverters. In this paper analysis, simulation and experimental results are presented.     

A Delay Decomposition Approach to Delay-Dependent Robust Passive Control for Takagi–Sugeno Fuzzy Nonlinear Systems

This paper is concerned with the problem of delay-dependent robust passive control for a fuzzy nonlinear system with time-varying delays. A Takagi–Sugeno fuzzy model approach is exploited to design a passive control for nonlinear systems with time-varying delay. By decomposing the delay interval into multiple equidistant subintervals, new Lyapunov–Krasovskii functionals (LKFs) are constructed on these intervals. Employing these new LKFs, a new robust passive control criterion is proposed in terms of linear matrix inequalities, which is dependent on the size of the time delay. We also design a state feedback controller that guarantees a robustly strictly passive closed-loop system for all admissible uncertainties. Finally, two numerical examples are given to illustrate the effectiveness of the developed techniques.     

Further Results on Dissipativity Criterion for Markovian Jump Discrete-Time Neural Networks with Two Delay Components Via Discrete Wirtinger Inequality Approach

This paper is concerned with strict \((\mathcal {Q}, \mathcal {S}, \mathcal {R})-\gamma \) - dissipativity and passivity analysis for discrete-time Markovian jump neural networks involving both leakage and discrete delays expressed in terms of two additive time-varying delay components. The discretized Wirtinger inequality is utilized to bound the forward difference of finite-sum term in the Lyapunov functional. By constructing a suitable Lyapunov–Krasovskii functional, sufficient conditions are derived to guarantee the dissipativity and passivity criteria of the proposed neural networks. These conditions are presented in terms of linear matrix inequalities (LMIs), which can be efficiently solved via LMI MATLAB Toolbox. Finally, numerical examples are given to illustrate the effectiveness of the proposed results.