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Inertia

About: Inertia is a research topic. Over the lifetime, 12006 publications have been published within this topic receiving 164291 citations.


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Journal ArticleDOI
01 Aug 1988
TL;DR: A suboptimal minimum energy method is presented to reduce a difficult 12-state, six-control nonlinear optimization to two independent, nonconflicting suboptimizations and a simulation example is provided to illustrate the degree of energy reduction possible using the optimal arm torque distribution.
Abstract: In designing a robot control system for dual arm configurations, the control engineer is faced with two challenges: to derive the equations of motion for a given situation, and to meet certain desired control requirements (for instance, minimum energy). The former may involve closed kinematic chains, such as the case when the two arms are grasping a common object. The latter usually involves nonlinear optimization. These issues are considered in the context of transporting an inertial load using two planar three-link arms. A generalized 'reduction transformation' is applied to the dynamics to remove the singularity in the system equations. A suboptimal minimum energy method is presented to reduce a difficult 12-state, six-control nonlinear optimization to two independent, nonconflicting suboptimizations. A simulation example is provided to illustrate the degree of energy reduction possible using the optimal arm torque distribution that was developed. >

47 citations

Journal ArticleDOI
TL;DR: In this paper, a closed-form solution developed by Kim in 1998 for calculating the reflection and transmission coefficients of a vertical slotted barrier, which is not well known because it is presented in his thesis, is compared with other closed-formed solutions developed by different authors.

47 citations

Proceedings ArticleDOI
29 Oct 2007
TL;DR: The strategy of linear descending inertia weight and the strategy of chaotic random inertia weight by introduced chaotic optimization mechanism into PSO algorithm are presented to makePSO algorithm has the characteristics of preferable convergence precision, quickly convergence velocity and better global search ability.
Abstract: The inertia weight is one of the parameter in particle swarm optimization algorithm. It gets important effect on balancing the global search and the local search in PSO. Basing on the linear descending inertia weight and the random inertia weight, this paper presents the strategy of chaotic descending inertia weight and the strategy of chaotic random inertia weight by introduced chaotic optimization mechanism into PSO algorithm. They make PSO algorithm has the characteristics of preferable convergence precision, quickly convergence velocity and better global search ability. The PSO using the chaotic random inertia weight performs especial outstanding comparing with the PSO using random inertia weight, owing to it has rough search stage and minute search stage alternately in all its evolutionary process. The chaotic inertia weight PSO using logistic mapping performs little better than that using tent mapping.

47 citations

Journal ArticleDOI
TL;DR: In this paper, an approach based on the manipulator generalized momentum is explored and applied to the dynamic modeling of a Stewart platform, where the generalized momentum was used to compute the kinetic component of the generalized force acting on each manipulator rigid body.

47 citations

Journal ArticleDOI
TL;DR: In this paper, the 3D nonlinear equations of motion of the suspended cable with moving mass are obtained via the Hamilton principle, and its transient linear planar dynamics is investigated.

47 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023886
20221,975
2021443
2020562
2019609
2018566