National University of Computer and Emerging Sciences

About: National University of Computer and Emerging Sciences is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Computer science & The Internet. The organization has 1506 authors who have published 2438 publications receiving 26786 citations.

Experimental validation of an integral sliding mode-based LQG for the pitch control of a UAV-mimicking platform

Abstract: In this paper, an enhanced Integral Sliding Mode-based Linear Quadratic Gaussian (ISM-LQG) controller has been proposed and verified in real-time on a Twin Rotor multi-input-multi-output MIMO System (TRMS). A TRMS serves as a suitable laboratory-based platform to evaluate the performance of control algorithms for complex Unmanned Aerial Vehicle (UAV) systems such as rotocraft. In the proposed scheme, an ISM enhancement to an LQG has been introduced, which attempts to overcome modelling inaccuracies and uncertainties. The novelty of the proposed control law lies in hybridizing a robust control approach with an optimal control law to achieve improved performance. Experimental results on the TRMS demonstrate that the ISM-LQG strategy significantly improves the tracking performance of the TRMS pitch and hence confirm the applicability and efficiency of the proposed scheme.

An Efficient and Simple Algorithm for Matrix Inversion

Abstract: In this paper, a new algorithm is proposed for finding inverse and determinant of a given matrix in one instance. The algorithm is straightforward in understanding and manual calculations. Computer implementation of the algorithm is extremely simple and is quite efficient in time and memory utilization. The algorithm is supported by an example. The number of multiplication/division performed by the algorithm is exactly; however, its efficiency lies in the simplicity of coding and minimal utilization of memory. Simple applicability and reduced execution time of the method is validated form the numerical experiments performed on test problems. The algorithm is applicable in the cases of pseudo inverses for non-square matrices and solution of system of linear equations with minor modification.

Compact Stars with Modified Gauss–Bonnet Tolman–Oppenheimer–Volkoff Equation

Abstract: We study compact stars for f( $$\mathcal{G}$$ ) gravity model using modified Tolman–Oppenheimer–Volkoff equation. Firstly, the hydrostatic equilibrium equations have been developed in the context of f( $$\mathcal{G}$$ ) gravity. Secondly, the profiles of energy density, pressure and mass of stars are investigated through two different equations of state models, p = ωρ5/3 and p = a(ρ – 4b), ρ being the energy density, ω, a and b are the specific constants. For f( $$\mathcal{G}$$ ) = α $${{\mathcal{G}}^{2}}$$ model with α being an arbitrary constant, the physical attributes of the compact objects have been discussed for the different values of model parameter α. It is concluded that in the framework of f( $$\mathcal{G}$$ ) gravity, neutron and strange stars follow physically accepted patterns and the results agree with those already available in literature.

A new modified Laplace decomposition method for higher order boundary value problems

Abstract: In this article, we suggest modified Laplace decomposition method for analytical solution of eighth-order boundary value problems (BVPs). The numerical application indicates the effectiveness and stability of the proposed algorithm. The efficiency of proposed method is examined with the help of linear and nonlinear problems.

Stabilizing Super Smart Grids Using V2G: A Probabilistic Analysis

Abstract: Due to reliability issues involved with the renewable energy integration and the random deviation of demand response profile from the generation response pattern, balancing of load flow and an assessment of transients stability become challenging research issues in super smart grids (SSGs). They are even more challenging, when an unexpected outage occurs due to occurrence of three phase (L-L-L) faults (TPFs), which also causes significant power quality disturbances in power systems. To address this problem, probabilistic and deterministic analysis based on super smart node (SSN), vehicle to grid (V2G) and continuous spinning reserve (CSR) are formulated to address the randomness complexity in terms of balancing load flow and an assessment of transient stability in SSGs. Through these techniques, future contingencies can be easily predicted in SSGs. Numerical results show that V2G probabilistic modeling provides better results for balancing of load flow and an enhancement in transients stability as compared to CSR deterministic modeling in SSGs. This observation is also validated by simulation results.