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Time-Domain Eyeball Fitting of Step Test Data

1 Time-Domain Eyeball Fitting of Step Test Data [Pg.503]

The most direct way of obtaining an empirical linear dynamic model of a process is to find the parameters (deadtime, time constant, and damping coefficient) that fit the experimentally obtained step response data. The process being identified is usually openloop, but experimental testing of closedloop systems is also possible. [Pg.503]

We put in a step disturbance m, and record the output variable x, as a function of time, as illustrated in Fig. 14.1. The quick-and-dirty engineering approach is to simply look at the shape of the x, curve and find some approximate transfer function Gjj, that would give the same type of step response. [Pg.503]

Probably 80 percent of all chemical engineering openloop processes can be modeled by a gain, deadtime, and one lag. [Pg.503]

The stead ystate gain Kp is easily obtained from the ratio of the final steady state change in the output Sx over the size of the step input Am. The deadtime can be easily read from the x, curve. The time constant can be estimated from the time it takes the output to reach 62.3 percent of the final steadystate change. [Pg.503]




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Data fitting

Eyeball

Fit testing

Step testing

Stepping test

Time domain

Time of Testing

Time-domain data

Timing of steps

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