Predictor Feedback Stabilization of Stochastic Linear Delayed Systems with Both Additive and Multiplicative Noises

In this paper we investigate memory control of stochastic linear delayed systems with both additive and multiplicative noises. A new formula is first presented to obtain the prediction vector from the system dynamics and then it is used for feedback to reduce the input delay in the original delayed system. To ensure the stability of closed‐loop system, some matrix inequality conditions are given that in the case of feasibility provide the stabilizing gain of the predictor controller. The proposed method is applied to stochastic quarter‐car model of an active suspension system to show the effectiveness of the approach.     

Parameter identification of linear multi-delay systems via a hybrid of block-pulse functions and Taylor’s polynomials

In this paper, an efficient and effective procedure is successfully developed for parameter identification of linear time-invariant multi-delay systems. The proposed framework is based on a hybrid of block-pulse functions and Taylor’s polynomials. Two upper error bounds corresponding to hybrid functions are established. The excellent properties of these functions together with the associated operational matrices of integration and delay are utilised to transform the original problem into a system of linear algebraic equations. The least squares method is then implemented for estimation of the unknown parameters. Several numerical experiments are investigated to demonstrate the usefulness and effectiveness of the proposed procedure. Easy implementation, simple operations and accurate solutions are the main features of the suggested approximation scheme.     

Size-dependent hygro–thermo–electro–mechanical vibration analysis of functionally graded piezoelectric nanobeams resting on Winkler–Pasternak foundation undergoing preload and magnetic field

Microsystem Technologies - In this study, nonlocal beam theory is utilized for vibration analysis of hygro–electro–thermo–mechanical of functionally graded material (FGM) nanobeam...     

Composite hierarchical antidisturbance control for a class of discrete‐time stochastic systems

In this paper, antidisturbance control and estimation problem are discussed for a class of discrete‐time stochastic systems with nonlinearity and multiple disturbances, which include the disturbance with partially known information and a sequence of random vectors. A disturbance observer is constructed to estimate the disturbance with partially known information. A composite hierarchical antidisturbance control scheme is proposed by combining disturbance observer and H_∞ control. It is proved that the 2 different disturbances can be rejected and attenuated, and the corresponding desired performances can be guaranteed for discrete‐time stochastic systems with known and unknown nonlinear dynamics, respectively. Simulation examples are given to demonstrate the effectiveness of the proposed scheme.     

Global output feedback control for a class of nonlinear systems with unknown homogenous growth condition

This paper investigates the problem of global control for a class of nonlinear systems via output feedback. The system nonlinearities satisfy the homogenous growth condition with unknown growth rate. First, a homogenous observer is constructed for estimating the system state. Then, two novel dynamic gains are presented to deal with the unknown growth rate. Subsequently, by adding a power integrator technique, a dynamic output feedback controller is designed to guarantee that all the signals of the closed‐loop system are bounded and the system states globally converge to origin. Finally, an example is provided to illustrate the validity of the proposed control scheme.     

DAWA: Defending against wormhole attack in MANETs by using fuzzy logic and artificial immune system

Mobile ad hoc networks (MANETs) are mobile networks, which are automatically outspread on a geographically limited region, without requiring any preexisting infrastructure. Mostly, nodes are both self-governed and self-organized without requiring a central monitoring. Because of their distributed characteristic, MANETs are vulnerable to a particular routing misbehavior, called wormhole attack. In wormhole attack, one attacker node tunnels packet from its position to the other attacker nodes. Such wormhole attack results in a fake route with fewer hop count. If source node selects this fictitious route, attacker nodes have the options of delivering the packets or dropping them. For this reason, this paper proposes an improvement over AODV routing protocol to design a wormhole-immune routing protocol. The proposed protocol called defending against wormhole attack (DAWA) employs fuzzy logic system and artificial immune system to defend against wormhole attacks. DAWA is evaluated through extensive simulations in the NS-2 environment. The results show that DAWA outperforms other existing solutions in terms of false negative ratio, false positive ratio, detection ratio, packet delivery ratio, packets loss ratio and packets drop ratio.     

An MLP-based representation of neural tensor networks for the RDF data models

In this paper, a new representation of neural tensor networks is presented. Recently, state-of-the-art neural tensor networks have been introduced to complete RDF knowledge bases. However, mathematical model representation of these networks is still a challenging problem, due to tensor parameters. To solve this problem, it is proposed that these networks can be represented as two-layer perceptron network. To complete the network topology, the traditional gradient based learning rule is then developed. It should be mentioned that for tensor networks there have been developed some learning rules which are complex in nature due to the complexity of the objective function used. Indeed, this paper is aimed to show that the tensor network can be viewed and represented by the two-layer feedforward neural network in its traditional form. The simulation results presented in the paper easily verify this claim.

     

Shear vibration and buckling of double-layer orthotropic nanoplates based on RPT resting on elastic foundations by DQM including surface effects

Microsystem Technologies - In this article, shear vibration and buckling of double-layer orthotropic nanoplates resting on elastic foundations are analyzed subjected to in-plane loadings including...