Simultaneous tuning of PID gains in multi-loop PID-based control systems using iterative feedback tuning methodology

Tuning a complex multi-loop PID based control system requires considerable expertise and experience. In today's power industry the number of available qualified tuners is dwindling due to retirements and promotions. There is a need in the industry for better tuning tools to address complex multivariable processes. Multi-loop PID tuning is the process of tuning a cluster of PID controllers applied to a multivariable process such as a power plant boiler/turbine system. In this paper several methods for the simultaneous automatic tuning of several loops are reviewed and one method, the IFT (iterative feedback tuning) method, is tested on a simple multivariable process and its control system. The process used in the testing is designed to resemble a simplified drum boiler/turbine process in a power plant and the control system is a cluster of six PID-type controllers arranged in a fashion similar to an actual plant control system. The structure includes cascade loops and a simple ratio controller. Although very simplified, the dynamics and cross-coupling of the process are similar to those in a real power plant. The IFT method is implemented in MATLAB/Simulink. The method utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed loop system for the boiler/turbine process, consisting of the nonlinear PID cluster and nonlinear power plant model. This means that in applications tuning would be done directly on the plant/controller configuration, without resorting to the closed-loop system model. However, the model of the PID cluster is needed to derive its linearized version and use the latter as part of the IFT tuner. The performance of the nonlinear PID cluster with optimal IFT tuned parameters is evaluated against its performance with parameters developed empirically. Based on the figure of merit for the control system performance, the IFT parameters deliver better performance than the empirical parameters.