Hey everyone!

I'm completely new on Control Systems, I came from a biotechnological background, but I'm interested on getting the transfer equation of a conductivity probe used in the laboratory to determine the blending time of a bioreactor. After comparing these results with the CFD values, I'm suspecting that the conductivity sensor is introducing some kind of delay and overestimating the results.

I was told I needed to determine the transfer equation of the sensor to perform a deconvolution of the conductivity experimental data to get the "real" data. The sensor was tested moving the probe between two solutions to get the data/curve for the step up (not in the experimental bioreactor) (analysis data). I started in Excel by adjusting the analysis data to a first-order step function where a tau (time-constant) was estimated from replications.

However, I have no idea how to continue to get the transfer equation. I tried some scripts in Matlab but the results make no sense. How Can I correct the conductivity experimental data set?

Many thanks in advance )

 

Hi PaCubo,

The easiest way is to ask the OEM for the equation.
If they don't have then you don't have much choice.
The other round about method is to get both input and out measured at the highest precision possible (like using a 6.5 digit calibrated multi meter) for the entire full scale range. IF you suspect there is a settling time or reaction time, use oscilloscope to measure the time lag. Once it settles and stabilises, then note the time delay. Now with the collected data use curve fitting methods to get your equation. Note that it will never be 100% confidence level. But you can target for closest to 100%. Even 99.96% may not be good enough for many process, depending up on the accuracy needs.

 

Transfer equations in control systems refer to mathematical models that describe the relationship between input and output signals of a system. These equations typically represent the dynamics of a system in terms of differential equations, Laplace transforms, or transfer functions. They are essential for analyzing and designing control systems, allowing engineers to predict system behavior, stability, and performance. Transfer equations help in selecting appropriate control strategies, tuning controllers, and optimizing system response. They are fundamental in various engineering applications, including robotics, automotive control, aerospace, and industrial automation, enabling precise and efficient system control and regulation.