LabVIEW code can be compiled to run on computers, (soft) real-time targets, and FPGAs (hard real-time targets), so students can easily and quickly step up to real industrial measurement and control problems without the need to learn new programming environments. Then a myRIO Student Embedded Device is used to control a real servo system. The first didactic step is a simulation with the Control Design and Simulation, as well as MathScript RT Modules. However, the mathematical background of sliding mode control is difficult compared to conventional PID control the SMC implementation for practical uses can be quite simple, as the presented example demonstrates. The graphical “coding” can help novice users to see through their algorithms. Both programming environments and the connection to NI hardware are relatively easy to use, therefore, ideal for education. The control of an actual system with LabVIEW and NI hardware provides an efficient implementation platform, using both LabVIEW’s graphical programming and the text-based m-file language MathScript RT. In other words, more time would need to be spent optimizing the PID controller to reduce the overshoot while maintaining a reasonable rise time (critically damped).The main contribution of this paper is to present the efficiency of LabVIEW in simulating and controlling a servo system with conventional methods (PI and PID control), as well as sliding mode control (SMC). For example, if the fan/tube plant were used for some sort of entertainment application, it may be permissible to have a looser tolerance given that the human eye has difficulty in distinguishing a difference of a few centimeters, however the underdamped system may be not be visually appealing.

Additionally, it is worth noting that depending on the application, it is important to set a realistic error tolerance with reasonable PID gains. In this project, the setup was improved by creating a dark contrast background to the orange ball, and filters were implemented to reduce noise in the system, but with an improved setup, machine vision could have been used to reach tighter error tolerances.

However, an improper setup can lead to inaccurate data acquisition, which can yield an unfavorable control system. Machine vision is a powerful tool that can be used across many applications to convert images/videos to quantitative data.

Labview collapse pid gains control