An MPPT (Maximum Power Point Tracking) plays a vital role in photovoltaic(PV) power generation system. Applying the optimum is significant way to achieve an efficient PV The methods’ efficiency counts on two factors, including perturbation period and amplitude. Nevertheless, realizing photovoltaic array very hard when natural conditions change, especially for temperature light intensity. This p...

In this preliminary work, left and right conjugate vectors are deened for nonsymmetric, nonsin-gular matrices A and some properties of these vectors are studied. A left conjugate direction (LCD) method for solving nonsymmetric systems of linear equations is proposed. The method reduces to the usual conjugate gradient method when A is symmetric positive deenite. A nite termination property of th...

In this paper, we proposed a new hybrid conjugate gradient algorithm for solving unconstrained optimization problems as convex combination of the Dai-Yuan algorithm, conjugate-descent and Hestenes-Stiefel algorithm. This is globally convergent satisfies sufficient descent condition by using strong Wolfe conditions. The numerical results show that nonlinear efficient robust.

We consider symmetric positive definite systems of linear equations with multiple right-hand sides. The seed conjugate gradient method solves one right-hand side with the conjugate gradient method and simultaneously projects over the Krylov subspace thus developed for the other right-hand sides. Then the next system is solved and used to seed the remaining ones. Rounding error in the conjugate ...

Conjugate Gradient (CG) method is the most prominent iterative mathematical technique that can be useful for optimization of both linear and non-linear systems due to its simplicity, low memory requirement, computational cost, global convergence properties. However, some classical CG methods have drawbacks which include weak convergence, poor numerical performance in terms number iterations CPU...

A hybrid global optimization method, the coevolutionary global optimization algorithm, is proposed which utilizes the self-organized critical state as the mean of diversification of search and the traditional conjugate gradient local minimization method as the mean of intensification of search. The former has been recently used by Boettcher and Percus (Artificial Intelligence 119 (2000) 275) to...

In this study it has been tried, to compare results and convergence rate of sensitivity analysis and conjugate gradient algorithms to reduce fuel consumption and increasing engine performance by optimizing the timing of opening and closing valves in XU7/L3 engine. In this study, considering the strength and accuracy of simulation GT-POWER software in researches on the internal combustion engine...

"In this paper, we present some hybrid methods for solving unconstrained optimization problems. These are defined using proper combinations of the search directions and included parameters in conjugate gradient quasi-Newton method Broyden-Fletcher-Goldfarb-Shanno (CG-BFGS). Their global convergence under Wolfe line is analyzed general objective functions. Numerical experiments show superiority ...