485,198 research outputs found
Design an intelligent controller for full vehicle nonlinear active suspension systems
The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives. The advantage of this controller is that it can handle the nonlinearities faster than other conventional controllers. The approach of the proposed controller is to minimize the vibrations on each corner of vehicle by supplying control forces to suspension system when travelling on rough road. The other purpose for using the NF controller for vehicle model is to reduce the body inclinations that are made during intensive manoeuvres including braking and cornering. A full vehicle nonlinear active suspension system is introduced and tested. The robustness of the proposed controller is being assessed by comparing with an optimal Fractional Order (FOPID) controller. The results show that the intelligent NF controller has improved the dynamic response measured by decreasing the cost function
Geometric phase in dephasing systems
Beyond the quantum Markov approximation, we calculate the geometric phase of
a two-level system driven by a quantized magnetic field subject to phase
dephasing. The phase reduces to the standard geometric phase in the weak
coupling limit and it involves the phase information of the environment in
general. In contrast with the geometric phase in dissipative systems, the
geometric phase acquired by the system can be observed on a long time scale. We
also show that with the system decohering to its pointer states, the geometric
phase factor tends to a sum over the phase factors pertaining to the pointer
states.Comment: 4 page
Dynamical Mean Field Theory of Nickelate Superlattices
Dynamical mean field methods are used to calculate the phase diagram,
many-body density of states, relative orbital occupancy and Fermi surface shape
for a realistic model of -based superlattices. The model is derived
from density functional band calculations and includes oxygen orbitals. The
combination of the on-site Hunds interaction and charge-transfer between the
transition metal and the oxygen orbitals is found to reduce the orbital
polarization far below the levels predicted either by band structure
calculations or by many-body analyses of Hubbard-type models which do not
explicitly include the oxygen orbitals. The findings indicate that
heterostructuring is unlikely to produce one band model physics and demonstrate
the fundamental inadequacy of modeling the physics of late transition metal
oxides with Hubbard-like models.Comment: Values of orbitals polarizations reported in Fig. 2 corrected. We
thank E. Benckiser and M. Wu for pointing out the error
Autonomous Locomotion Mode Transition Simulation of a Track-legged Quadruped Robot Step Negotiation
Multi-modal locomotion (e.g. terrestrial, aerial, and aquatic) is gaining
increasing interest in robotics research as it improves the robots
environmental adaptability, locomotion versatility, and operational
flexibility. Within the terrestrial multiple locomotion robots, the advantage
of hybrid robots stems from their multiple (two or more) locomotion modes,
among which robots can select from depending on the encountering terrain
conditions. However, there are many challenges in improving the autonomy of the
locomotion mode transition between their multiple locomotion modes. This work
proposed a method to realize an autonomous locomotion mode transition of a
track-legged quadruped robot steps negotiation. The autonomy of the
decision-making process was realized by the proposed criterion to comparing
energy performances of the rolling and walking locomotion modes. Two climbing
gaits were proposed to achieve smooth steps negotiation behaviours for energy
evaluation purposes. Simulations showed autonomous locomotion mode transitions
were realized for negotiations of steps with different height. The proposed
method is generic enough to be utilized to other hybrid robots after some
pre-studies of their locomotion energy performances
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