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Fuzzy sliding mode control design of Markovian jump systems with time-varying delay
Sakthivel, R.,Sakthivel, R.,Nithya, V.,Selvaraj, P.,Kwon, O.M. Elsevier 2018 Journal of the Franklin Institute Vol.355 No.14
<P><B>Abstract</B></P> <P>This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.</P>
Sakthivel, Rathinasamy,Sakthivel, Ramalingam,Kaviarasan, Boomipalagan,Wang, Chao,Ma, Yong-Ki Hindawi Limited 2018 Complexity Vol.2018 No.-
<P>The problem of robust nonfragile synchronization is investigated in this paper for a class of complex dynamical networks subject to semi-Markov jumping outer coupling, time-varying coupling delay, randomly occurring gain variation, and stochastic noise over a desired finite-time interval. In particular, the network topology is assumed to follow a semi-Markov process such that it may switch from one to another at different instants. In this paper, the random gain variation is represented by a stochastic variable that is assumed to satisfy the Bernoulli distribution with white sequences. Based on these hypotheses and the Lyapunov-Krasovskii stability theory, a new finite-time stochastic synchronization criterion is established for the considered network in terms of linear matrix inequalities. Moreover, the control design parameters that guarantee the required criterion are computed by solving a set of linear matrix inequality constraints. An illustrative example is finally given to show the effectiveness and advantages of the developed analytical results.</P>
Sakthivel, R.,Anbuvithya, R.,Mathiyalagan, K.,Ma, Y.K.,Prakash, P. Elsevier [etc.] 2016 Applied Mathematics and Computation Vol.275 No.-
<P>This paper is concerned with anti-synchronization results for a class of memristor-based bidirectional associate memory (BAM) neural networks with different memductance functions and time-varying delays. Based on drive-response system concept, differential inclusions theory and Lyapunov stability theory, some sufficient conditions are obtained to guarantee the reliable asymptotic anti-synchronization criterion for memristor-based BAM networks. The memristive BAM neural network is formulated for two types of memductance functions. Sufficient results are derived in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed criterion is demonstrated through numerical example. (C) 2015 Elsevier Inc. All rights reserved.</P>
New exponential stability criteria for stochastic BAM neural networks with impulses
Sakthivel, R,Samidurai, R,Anthoni, S M Royal Swedish Academy of Sciences 2010 Physica scripta Vol.82 No.4
<P>In this paper, we study the global exponential stability of time-delayed stochastic bidirectional associative memory neural networks with impulses and Markovian jumping parameters. A generalized activation function is considered, and traditional assumptions on the boundedness, monotony and differentiability of activation functions are removed. We obtain a new set of sufficient conditions in terms of linear matrix inequalities, which ensures the global exponential stability of the unique equilibrium point for stochastic BAM neural networks with impulses. The Lyapunov function method with the Itô differential rule is employed for achieving the required result. Moreover, a numerical example is provided to show that the proposed result improves the allowable upper bound of delays over some existing results in the literature.</P>
Asymptotic stability of delayed stochastic genetic regulatory networks with impulses
Sakthivel, R,Raja, R,Marshal Anthoni, S Royal Swedish Academy of Sciences 2010 Physica scripta Vol.82 No.5
<P>In this paper, the asymptotic stability analysis problem is considered for a class of delayed stochastic genetic regulatory networks with impulses. Based on the Lyapunov stability technique and stochastic analysis theory, stability criteria are proposed in terms of linear matrix inequalities (LMI). It is shown that the addressed stochastic genetic regulatory networks are globally asymptotically stable if four LMIs are feasible, where the feasibility of LMIs can be readily checked by Matlab LMI toolbox. Finally, a numerical example is given to demonstrate the usefulness of the proposed result.</P>
Sakthivel, Pillanatham Civalingam,Kamra, Devki Nandan,Agarwal, Neeta,Chaudhary, Chandra Asian Australasian Association of Animal Productio 2012 Animal Bioscience Vol.25 No.6
Nitrate can serve as a terminal electron acceptor in place of carbon dioxide and inhibit methane emission in the rumen and nitrate reducing bacteria might help enhance the reduction of nitrate/nitrite, which depends on the type of feed offered to animals. In this study the effects of three levels of sodium nitrate (0, 5, 10 mM) on fermentation of three diets varying in their wheat straw to concentrate ratio (700:300, low concentrate, LC; 500:500, medium concentrate, MC and 300:700, high concentrate, HC diet) were investigated in vitro using buffalo rumen liquor as inoculum. Nitrate reducing bacteria, isolated from the rumen of buffalo were tested as a probiotic to study if it could help in enhancing methane inhibition in vitro. Inclusion of sodium nitrate at 5 or 10 mM reduced (p<0.01) methane production (9.56, 7.93 vs. 21.76 ml/g DM; 12.20, 10.42 vs. 25.76 ml/g DM; 15.49, 12.33 vs. 26.86 ml/g DM) in LC, MC and HC diets, respectively. Inclusion of nitrate at both 5 and 10 mM also reduced (p<0.01) gas production in all the diets, but in vitro true digestibility (IVTD) of feed reduced (p<0.05) only in LC and MC diets. In the medium at 10 mM sodium nitrate level, there was 0.76 to 1.18 mM of residual nitrate and nitrite (p<0.01) also accumulated. In an attempt to eliminate residual nitrate and nitrite in the medium, the nitrate reducing bacteria were isolated from buffalo adapted to nitrate feeding and introduced individually (3 ml containing 1.2 to $2.3{\times}10^6$ cfu/ml) into in vitro incubations containing the MC diet with 10 mM sodium nitrate. Addition of live culture of NRBB 57 resulted in complete removal of nitrate and nitrite from the medium with a further reduction in methane and no effect on IVTD compared to the control treatments containing nitrate with autoclaved cultures or nitrate without any culture. The data revealed that nitrate reducing bacteria can be used as probiotic to prevent the accumulation of nitrite when sodium nitrate is used to reduce in vitro methane emissions.