Robust Fractional-Order PI Controller with Ziegler-Nichols Rules

In process control applications, above 90% of the controllers are of PID type. This paper proposed a robust PI controller with fractional-order integrator. The PI parameters were obtained using classical Ziegler-Nichols rules but enhanced with the application of error filter cascaded to the fractional-order PI. The controller was applied on steam temperature process that was described by FOPDT transfer function. The process can be classified as lag dominating process with very small relative dead-time. The proposed control scheme was compared with other PI controller tuned using Ziegler-Nichols and AMIGO rules. Other PI controller with fractional-order integrator known as F-MIGO was also considered. All the controllers were subjected to set point change and load disturbance tests. The performance was measured using Integral of Squared Error (ISE) and Integral of Control Signal (ICO). The proposed controller produced best performance for all the tests with the least ISE index.

Robust Steam Temperature Regulation for Distillation of Essential Oil Extraction Process using Hybrid Fuzzy-PD plus PID Controller

This paper presents a hybrid fuzzy-PD plus PID (HFPP) controller and its application to steam distillation process for essential oil extraction system. Steam temperature is one of the most significant parameters that can influence the composition of essential oil yield. Due to parameter variations and changes in operation conditions during distillation, a robust steam temperature controller becomes nontrivial to avoid the degradation of essential oil quality. Initially, the PRBS input is triggered to the system and output of steam temperature is modeled using ARX model structure. The parameter estimation and tuning method is adopted by simulation using HFPP controller scheme. The effectiveness and robustness of proposed controller technique is validated by real time implementation to the system. The performance of HFPP using 25 and 49 fuzzy rules is compared. The experimental result demonstrates the proposed HFPP using 49 fuzzy rules achieves a better, consistent and robust controller compared to PID when considering the test on tracking the set point and the effects due to disturbance.