Adaptive Feedforward Control of Wastewater Neutralization.

• Main Author: Balhoff, Richard Albert
• Format: Text
• Language: English
• Published: LSU Scholarly Repository 1982
• Subjects: Engineering; chemical; Carbonic acid
• Online Access: https://repository.lsu.edu/gradschool_disstheses/3745; https://doi.org/10.31390/gradschool_disstheses.3745; https://repository.lsu.edu/context/gradschool_disstheses/article/4744/viewcontent/8229488.pdf

The purpose of this dissertation is to show the development and testing of an adaptive feedforward control of a wastewater neutralization process. The adaptive controller is compared to a nonlinear proportional-integral-derivative (NPID) controller developed by Shinskey (1970). The process and controllers were simulated digitally. The adaptive controller utilizes two pH probes, a feedforward probe and a feedback probe (this measurement is used in the adaptive gain calculation). The feedback measurement provides the adaptive controller with a form of reset action. Probe noise and lag, valve hysteresis and lag, and dead time were included in the simulation. The process simulated for control combines a strong (hydrochloric) and weak (carbonic) acid neutralized by a strong base (sodium hydroxide). The adaptive controller was shown to give superior responses both for step changes in the strong acid and the buffer (weak acid) concentration. The tuning constant limits for the adaptive controller are correlated versus the buffer concentration of the incoming solution for a base case. The sensitivity of the adaptive control to changes in certain parameters (probe noise and lag, valve hysteresis and lag, and dead time) are illustrated. Also shown is the effect of a step change in flow rate to the system. Noise in the feedforward pH probe and the dead time between the reagent addition and the feedback probe had the largest effect on the adaptive controller performance. Efforts to solve the many problems involved in the control of the pH of effluent streams have failed to yield acceptable control algorithm for this very difficult process. This research provides a significant step toward the solution of these problems. An additional bonus of the adaptive controller is the use of only two tuning parameters (many controllers in use today require five or more tuning parameters).