Inverse kinematics is an important basic theory in walking control of biped robot. This study focuses on the parameter setting using the improved algorithm in inverse kinematics. By analyzing the process of whether ca...
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Inverse kinematics is an important basic theory in walking control of biped robot. This study focuses on the parameter setting using the improved algorithm in inverse kinematics. By analyzing the process of whether can the robot legs arrive at the expected positions from different initial positions, the parameter value range is determined. It must be noted that, the parameter values exhibit clear physical significance. The robot legs can move stably within the allowable value range. Furthermore, the superiority of the improved algorithm was validated by 3D simulation of leg motion. Moreover, the present study can provide theoretical basis for optimizing the leg motion of biped robot and developing the related prototype.
Optimal reactive power planning is an important task for experts and industrials to ensure the reliability of modern power systems. Actually, the structure of practical power systems becomes dynamic and characterised ...
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Optimal reactive power planning is an important task for experts and industrials to ensure the reliability of modern power systems. Actually, the structure of practical power systems becomes dynamic and characterised by uncertainty in load and non-linear characteristic of various elements of power systems such as constraints associated to thermal units, constraints associated with FACTS devices and renewable sources. This study introduces an intelligent strategy based new metaheuristic named Salp swarm algorithm (SSA) to improve the solution of reactive power dispatch by optimising the total power loss, the total voltage deviation individually and simultaneously considering static VAR compensators (SVCs). To improve the efficiency of the original algorithm in solving large test systems, a sub SSA is formed to optimise the various objective functions based on a grouped control variable. In this study, four grouped swarms named SSA_PG for active power, SSA_VG for voltages, SSA_Ti for Tap transformers, and SSA_SVC for SVCs are formed to operate in a flexible structure to minimise a specified objective function. The proposed intelligent planning strategy validated on the IEEE 30 bus and to the large electrical test system 114 Bus of the Algerian network at normal condition and considering critical situations such as margin loading stability and contingency. Results found using the proposed strategy compared to those cited recently in the literature proves its particularity in terms of solution quality and convergence characteristics.
作者：
Woo, HCTaegu Univ
Sch Comp & Commun Engn Jinryang Kyungsan Kyungp 712714 South Korea
The performance of a stochastic gradient adaptive filter can be significantly improved by introducing a forgetting factor. The complexity of the original algorithm can also be reduced by using only the signs of error ...
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The performance of a stochastic gradient adaptive filter can be significantly improved by introducing a forgetting factor. The complexity of the original algorithm can also be reduced by using only the signs of error signals and input signals in the gradient adaptive step size computation.
In this paper we discuss the computational aspects of two algorithms due to E. I. Jury for determining if all the zeros of a polynomial with integer coefficients lie within the unit circle. We show that Jury's ori...
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In this paper we discuss the computational aspects of two algorithms due to E. I. Jury for determining if all the zeros of a polynomial with integer coefficients lie within the unit circle. We show that Jury's original algorithm asymptotically requires an exponential amount of computing time when variable-precision arithmetic is employed. We show that his modified algorithm requires only a polynomially bounded amount of computing time when variable-precision arithmetic is employed. Finally we produce a congruence arithmetic algorithm analogous to Jury's modified algorithm which requires less computing time than Jury's modified algorithm.
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