Strategies for enhancing nonlinear internal model control of pH processes

Control of neutralization processes is very difficult due to nonlinear dyna mics, different types of disturbances and modeling errors. The objective of the paper is to evaluate two strategies (augmented internal model control, AuIMC and adaptive internal model control, AdIMC) for enhancing pH control by nonlinear internal model control (NIMC). A NIMC controller is derived d irectly from input output linearization. The AuIMC is composed of NIMC and an additional loop through which the difference between the process and mod el outputs is fed back and added to the input of the controller. For the Ad IMC, an adaptive law with two tuning parameters is proposed for estimating the unknown parameter. Both AuIMC and AdIMC are extensively tested via simu lation for pH neutralization. The theoretical and simulation results show t hat both the proposed strategies can reduce the effect of modeling errors a nd disturbances, and thereby enhance the performance of NIMC for pH process es.