Dead algorithm

This problem is known as dead time. To offset this effect, an algorithm is used to adjust the actual number of events into a true number of events. Since the numbers of ions represent ion abundances, the correction adjusts only abundances of ions before a mass spectrum is printed. 

The simplest data reduction algorithm for FIDs consists in averaging the magnitudes of the complex FID signal over a data window positioned within its starting portion (Fig. 26). The window can be freely positioned in a way to cut out any dead-time distortions and, at the same time, minimize field-fluctuation effects. 

Fig. 6.9 shows the control algorithm and a process w/ith a phase shift of the first order and a dead time. The dynamics of the measuring device and the control elements (in our case the evaporator and the power supply) are... 

As Van der Grinten developed his estimation algorithm for real time process control he also introduced a dead time , the time between sampling and availability of the analytical result. As a measure of reconstruction efficiency he defined the measurability factor... 

Leemans described a sampling scheme based on these algorithms that considers sampling frequency, sampling time, dead time and accuracy of the method of analysis to obtain optimal information yield or maximal profit when controlling a factory. 

DAHLIN<44) suggested that, in order to avoid the large overshoots and oscillatory behaviour which are characteristic of the deadbeat algorithm, the specification of the system closed-loop response to a step change in set point should be the same as that for a first-order system with dead time. The first-order time constant can then be employed as a design parameter which can be adjusted to give the desired closed-loop response. Hence ... 

W.L. Luyben, Effect of derivative algorithm and tuning selection on the PID control of dead-time processes, Ind. Eng. Chem. Res. 40 (2001) 3605-3611. 

A Simulation Study on the Use of a Dead-Time Compensation Algorithm for Closed-Loop Conversion Control of Continuous Emulsion Polymerization Reactors... 

The objective of this paper is to illustrate, by simulation of the vinyl acetate system, the utility of the analytical predictor algorithm for dead-time compensation to regulatory control of continuous emulsion polymerization in a series of CSTR s utilizing initiator flow rate as the manipulated variable. 

If operated on clean, dry plant air, pneumatic controllers offer good performance and are extremely reliable. In many cases, however, plant air is neither clean nor dry. A poor-quality air supply will cause unreliable performance of pneumatic controllers, pneumatic field measurement devices, and final control elements. The main shortcoming of the pneumatic controller is its lack of flexibility when compared to modem electronic controller designs. Increased range of adjustability, choice of alternative control algorithms, the communication link to the control system, and other features and services provided by the electronic controller make it a superior choice in most of todays applications. Controller performance is also affected by the time delay induced by pneumatic tubing mns. For example, a 100-m run of 6.35-mm ( -in) tubing will typically cause 5 s of apparent process dead time, which will limit the control performance of fast processes such as flows and pressures. 

When PID algorithms are implemented digitally, what used to be integration becomes summation, and what used to be differentiation becomes difference. The scan period of DCS systems is fixed at around 0.5 seconds or is selectable for each loop from under 0.1 to over 30 seconds. As digital controllers do not continuously evaluate the measurements, but look at them intermittently, this increases the dead time of the loop by two "scan periods" which are needed to calculate the "present" and the "previous" error. 

A related approach which has been used successfully in industrial applications occurs in discrete-time control. Both Dahlin (43) and Higham (44) have developed a digital control algorithm which in essence specifies the closed loop response to be first order plus dead time. The effective time constant of the closed loop response is a tuning parameter. If z-transforms are used in place of s-transforms in equation (11), we arrive at a digital feedback controller which includes dead time compensation. This dead time predictor, however, is sensitive to errors in the assumed dead time. Note that in the digital approach the closed loop response is explicitly specified, which removes some of the uncertainties occurring in the traditional root locus technique. 

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