124 research outputs found
Computer numerical control vertical machining centre feed drive modelling using the transmission line technique
This study presents a novel application of the Transmission Line Matrix Method (TLM) for the modelling of the dynamic behaviour of non-linear hybrid systems for CNC machine tool drives. The application of the TLM technique implies the dividing of the ball-screw shaft into a number of identical elements in order to achieve the synchronisation of events in the simulation, and to provide an acceptable resolution according to the maximum frequency of interest. This entails the use of a high performance computing system with due consideration to the small time steps being applied in the simulation. Generally, the analysis of torsion and axial dynamic effects on a shaft implies the development of independent simulated models. This study presents a new procedure for the modelling of a ball-screw shaft by the synchronisation of the axial and torsion dynamics into the same model. The model parameters were obtained with equipments such as laser interferometer, ball bar, electronic levels, signal acquisition systems etc. The MTLM models for single and two-axis configurations have been simulated and matches well with the measured responses of machines. The new modelling approach designated the Modified Transmission Line Method (MTLM) extends the TLM approach retaining all its inherent qualities but gives improved convergence and processing speeds. Further work since, not the subject of this paper, have identified its potential for real time application
PI controller tuning for load disturbance rejection using constrained optimization
© 2016, Springer-Verlag Berlin Heidelberg. In this paper, a simple and effective PI controller tuning method is presented. To take both performance requirements and robustness issues into consideration, the design technique is based on optimization of load disturbance rejection with a constraint either on the gain margin or phase margin. In addition, a simplified form of the resulting tuning formulae is obtained for first order plus dead time models. To demonstrate the ability of the proposed tuning technique in dealing with a wide range of plants, simulation results for several examples, including integrating, non-minimum phase and long dead time models, are provided
Growth of solid conical structures during multistage drying of sessile poly(ethylene oxide) droplets
Sessile droplets of aqueous poly(ethylene oxide) solution, with average
molecular weight of 100 kDa, are monitored during evaporative drying at ambient
conditions over a range of initial concentrations . For all droplets with
, central conical structures, which can be hollow and nearly 50%
taller than the initial droplet, are formed during a growth stage. Although the
formation of superficially similar structures has been explained for
glass-forming polymers using a skin-buckling model which predicts the droplet
to have constant surface area during the growth stage (L. Pauchard and C.
Allain, Europhys. Lett., 2003, 62, 897-903), we demonstrate that this model is
not applicable here as the surface area is shown to increase during growth for
all . We interpret our experimental data using a proposed drying and
deposition process comprising the four stages: pinned drying; receding contact
line; bootstrap growth, during which the liquid droplet is lifted upon
freshly-precipitated solid; and late drying. Additional predictions of our
model, including a criterion for predicting whether a conical structure will
form, compare favourably with observations. We discuss how the specific
chemical and physical properties of PEO, in particular its amphiphilic nature,
its tendency to form crystalline spherulites rather than an amorphous glass at
high concentrations and its anomalous surface tension values for MW = 100 kDa
may be critical to the observed drying process.Comment: 19 pages, 9 figures, Phys.Chem.Chem.Phys (accepted
Modification of static bending strength properties of Eucalyptus grandis heat-treated wood
PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM
Designing real time model mobile monitoring system for model predictive control in a nonlinear continuous stirred tank reactor
- …