Nonlinear Control of a Helio-Crane Laboratory Device

When designing control loops, we often encounter non-linear systems that have much more complex dynamics than linear systems. This means that with classical control algorithms we cannot guarantee that the control loop works sufficiently well over the entire operating range. Therefore, in this paper we focus on controlling a nonlinear dynamic system with more advanced nonlinear controllers. All experiments were performed on a helio-crane laboratory device. The device exhibits nonlinear operation and rather oscillatory behaviour and is therefore particularly well suited for testing developed nonlinear controllers. In this work we have developed and tested three controllers: PID controller with optimised parameters, fuzzy cloud-based predictive functional controller (FCPFC) and NARMA L2 controller. We first present the results for each controller, which we compare to determine the best type of controller for our nonlinear problem. The goal is not only to find the best controller in terms of efficiency, but we also consider the time required to develop the control solution. In this way, each of the controllers has its own advantages and disadvantages.