Rajasthan Technical University

About: Rajasthan Technical University is a education organization based out in Kota, Rajasthan, India. It is known for research contribution in the topics: Photovoltaic system & PID controller. The organization has 716 authors who have published 1084 publications receiving 4530 citations. The organization is also known as: RTU.

Some expansion formulas for incomplete H- and H̅-functions involving Bessel functions

Abstract: In this paper, we assess an integral containing incomplete H-functions and utilize it to build up an expansion formula for the incomplete H-functions including the Bessel function. Next, we evaluate an integral containing incomplete H-functions and use it to develop an expansion formula for the incomplete H-functions including the Bessel function. The outcomes introduced in this paper are general in nature, and several particular cases can be acquired by giving specific values to the parameters engaged with the principle results. As particular cases, we derive expansions for the incomplete Meijer ${}^{(\Gamma )}G$ -function, Fox–Wright ${}_{p}\Psi _{q}^{(\Gamma )}$ -function, and generalized hypergeometric ${}_{p}\Gamma _{q}$ function.

Synthesis of balanced quaternary reversible logic circuit

Abstract: Binary number system based digital logic design has been in use for long with phenomenal increase in circuit sizes, working with binary logic system is becoming increasingly difficult. Multi-valued logic system reduces the significant amount of design effort. Multi-valued ternary logic under GF (3) and quaternary logic under GF (4) are available in the literature, but circuit design based on these logic systems is very few. As traditional computing devices based on irreversible logic are approaching their limit in terms of heat dissipation, power and speed requirement. Reversible computing is emerging as an alternative technology. Usage of multi-valued logic for irreversible computing is also growing. Ternary and quaternary logic based reversible gate have been proposed recently. Ternary logic based design has further been enhanced using balanced logic levels. But, the same is not available for quaternary logic. In this paper, we propose balanced quaternary logic and synthesis approach, which offers significant advantages in logic design. Small circuits like adder subtractor have also been designed based on that approach. We feel that balanced logic based approach will open a new era in multivalued logic design.

Optimal LFC system of interconnected thermal power plants using hybrid particle swarm optimization-pattern search algorithm (hPSO-PS)

Abstract: In this paper, the application of pattern search algorithm (PS) in conjunction with the well known algorithm “particle swarm optimization” (PSO) has been explored in the area of automatic generation control for multi area interconnected thermal power system. The resultant hybrid algorithm named as “hPSO-PS” has been applied to optimize the parameters of proportional integral controllers in the two areas of power plant. The control optimization problem has been defined with lower and upper bounds of the controller's parameters along with the ITAE as an objective function. The simulation results have also been compared with the previously proposed PSO/PI and PSO/PID approach in the literature and the results show that the approach hPSO-PS/PI proposed here provides far better results than PSO/PI and PSO/PID for the same system and same ITAE as an objective function in terms of the less settling times and peak overshoots, better dynamic responses, quick response of returning back to the zero frequency as well as the tie line power deviations with fewer oscillations. The results have been simulated in MATLAB environment.

A Particle Grey Wolf Hybrid Algorithm for Workflow Scheduling in Cloud Computing

Abstract: A workflow consists of a set of tasks that are dependent on each other and scheduling these dependent tasks to the virtual machines is one of the complex problems in cloud computing. Moreover, workflow scheduling becomes more complex with the increasing number of tasks and virtual machines and considered to be an NP-hard problem. Therefore, the meta-heuristic approaches have been used to find out optimal scheduling of workflow schedules. The proposed algorithm named PSO–GWO is the combination of two well-known meta-heuristic algorithms Particle Swarm Optimization and Grey Wolf Optimization. The experiment result shows that the PSO–GWO algorithm decreases the average total execution cost and average total execution time in comparison to standard Particle Swarm Optimization and Grey Wolf Optimization algorithm.

Differential evolution algorithm using stochastic mutation

Abstract: Differential Evolution (DE) Algorithm is a population-based meta-heuristic for solving various complex optimization problems. Mutation scale factor and Crossover constant are the two important control parameters of the algorithm which are used to direct the search process to the global optima. Fine tuning of both the parameters controls the performance of the algorithm. Literature suggests that due to large step sizes, DE is unable to exploit the promising search space. So, to improve exploitation capability of the algorithm, by taking inspiration from levy flight random walk, a new mutation scale factor, namely stochastic mutation factor is proposed and incorporated with DE. The proposed strategy is named as Differential Evolution Algorithm using Stochastic Mutation (DESMU). Further, to increase the exploration capability of the algorithm, a limit is associated with every solution to count the number of not updating iterations. If this count crosses the pre-defined limit then the solution is randomly initialized. The proposed algorithm is tested over 15 benchmark test functions and compared with basic (DE), and two of its variants namely Scale Factor Local Search Differential Evolution (SFLSDE) and Self-adaptive Differential Evolution (SADE). The results reveal that DESMU is a competitive variant of DE.