Adaptive Fuzzy Feedforward-Feedback Controller Applied to a Level Prototype

Abstract

Loads are one of the most common disturbances sources experienced in chemical processes, causing deterioration of control performance and even affecting product quality. If such inputs are measurable, implementing a feedforward controller can improve signicantly the control performance, reducing the deviation of the process variable (PV). Nevertheless its effectiveness is highly dependent on satisfactory identication of process and disturbance models, task that is time consuming and quite difficult especially when they are non-linear. To cope with such situation, it is usual to deploy of adaptive techniques capable of handling nonlinearity and enhance the control performance. For such matter, it was implemented an adaptive fuzzy strategy able to correlate process and disturbance parameters according to PV value in a feedforward-feedback level control loop applied to an experimental prototype. The fuzzy strategy was used to adapt the lead-lag compensator parameters and it required fewer experiments than others techniques to adjust the parameters, showing a considerable performance improvement. The performances of classical feedback (FB) and feedforward-feedback (FFFB) control strategies were compared to the proposed adaptive fuzzy feedforward-feedback (A4FB) control loop under different servo and regulatory control situations. It was showed that A4FB increased the disturbance rejection in comparison to others control loops evaluated and, combined with its relatively simple implementation, it is an advantageous control loop for practical purposes.