Parameter identification studies

The samples without defensive film coat were studied by the method of concentration pulses (MCP) at pressure 0.2 Torr within the range of temperatures 370 -596 °C in order to determine the hydrogen permeability parameters of stainless steel (12X18H10T). The knowledge of these parameters allowed to simplify the problem of parameter identification for titanium nitride. The samples with titanium nitride covering were studied by method of permeability at pressures 0.5-249 Torr and the temperatures 380-670 °C. 

Finally, a word of caution is in order. Few systematic experimental studies have been made in this field so far and the database acquired is still limited. A small number of adsorbents has been investigated. It is difficult to assess the consistency of the published results and their accuracy. A number of the correlations used in the intermediate calculations are of limited accuracy when applied to porous media. The alternate approach of performing parameter identification with raw calculation power cannot give convincing results. The approach holds great promises but independent determinations of the kinetic parameters is dearly needed. 

In the case of composite laminates, new problems linked to the anisotropy of diffusion paths, the eventual role of interfacial diffusion and the role of pre-existing or swelling-induced damage appeared in the mid-1970s. The interest was mainly focused on the effect of humidity on carbon fibre/amine crosslinked epoxy composites of aeronautical interest. For the pioneers of this research (Shen and Springer, 1976), the determination of diffusion kinetic laws appeared as the key objective. Various studies revealed that, in certain cases, diffusion in composites caimot be modelled by a simple Pick s law and that Langmuir s equation is more appropriate. Carter and Kibler (1978) proposed a method for the parameter identification. At the end of the 1970s, the kinetic analysis of water diffusion into composites became a worldwide research objective. Related experimental results can be summarized as follows. 

For more recent and complex mechanisms, the fact is that despite the best efforts of experimental and theoretical kineticists, a large proportion of the elementary steps will have never been studied individually and are likely to be deduced from similar reactions or by kinetic methods such as those proposed by Atkinsmi (Atkinson 1986, 1987 Kwok and Atkinson 1995). Such approximation methods are unlikely to achieve the same degree of accuracy as fundamental theoretical or experimental studies. However, we will see later in Chap. 5 that the methods of uncertainty and sensitivity analysis can aid the process of important parameter identification, so that strongly influential parameters from this estimated group can be targeted by further kinetic studies. 

A practical case study is presented in Chap. 9 where friction-induced vibration in a lead screw drive is the cause of excessive audible noise. Using a complete dynamical model of this drive, a two-stage system parameter identification and fine-tuning method is developed to estimate the parameters of the velocity-dependent coefficient of friction model. The verified mathematical model is then used to study the role of various system parameters on the stability of the system and on the amplitude of vibrations. These smdies lead to possible design modifications that can solve the system s excessive noise problem. 

Fitting Dynamic Models to E erimental Data In developing empirical transfer functions, it is necessary to identify model parameters from experimental data. There are a number of approaches to process identification that have been pubhshed. The simplest approach involves introducing a step test into the process and recording the response of the process, as illustrated in Fig. 8-21. The i s in the figure represent the recorded data. For purposes of illustration, the process under study will be assumed to be first order with deadtime and have the transfer func tion ... 

In the present study, we propose a tuning method for PID controllers and apply the method to control the PBL process in LG chemicals Co. located in Yeochun. In the tuning method proposed in the present work, we first find the approximated process model after each batch by a closed-loop Identification method using operating data and then compute optimum tuning parameters of PID controllers based on GA (Genetic Algorithm) method. 

---