Decentralized Adaptive PI with Adaptive Interaction Algorithm of Wastewater Treatment Plant
DOI:
https://doi.org/10.11113/jt.v67.2837Keywords:
Adaptive decentralized PI, adaptive interaction algorithmAbstract
Wastewater treatment plant (WWTP) is highly known with the variation and uncertainty of the parameters, making them a challenge to be tuned and controlled. In this paper, an adaptive decentralized PI controller is developed for nonlinear activated sludge WWTP. The work is highlighted in auto-tuning the PI control parameters in satisfying straighten effluent quality and hence optimizing the nitrogen removal. The PI controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. The error function is minimized directly by approximate Frechet tuning algorithm without explicit estimation of the model. The effectiveness of the proposed controller is then validated by comparing the performance of activated sludge process to the benchmark PI under three different weather conditions with realistic variations in influent flow rate and composition. The algorithm is effectively applied in activated sludge system with improved dynamic performances in effluent quality index and energy consumed of Benchmark Simulation Model No.1.
References
Luyben, W. L. 1986. Simple Method for Tuning SISO Controllers in Multivariable Systems. Ind. Eng. Chem. ProcessDes. Dev.
Samuelsson, P., B. Halvarsson, and B. Carlsson. 2005. Interaction Analysis and Control Structure Selection in a Wastewater Treatment Plant Model. IEEE Transactions on Control System Technology.
Alex, J. , L. Benedetti, J. Copp, K. Gernaey, U. Jeppsson, I. Nopens, et al. 2008. Benchmark Simulation Model No. 1 (BSM1).
Copp, J. B. 2002. COST Action 624: The COST Simulation Benchmark. Description and Simulation Manual: Office for Official Publications of the European Communities.
Henze, M., C. P. L. G. Jr., W. Gujer, G. V. R. Marais, and T. Matsuo. 1987. Activated Sludge Model No.1.
Takács, I., G. G. Patry, and D. Nolasco. 1991. A dynamic model of thc clarification-thickening process. Water Research. 25: 1263–1271.
Rojas, J. D., X. Flores-Alsina, U. Jeppsson, and R. Vilanova. 2012. Application of Multivariate Virtual Reference Feedback Tuning for Wastewater Treatment Plant Control. Control Engineering Practice. 20: 499–510.
Pomerleau, D. and A. Pomerleau. 2001. Guidelines for the Tuning and the Evaluation of Decentralized and Decoupling Controllers for Process with Recirculation. ISA Transactions. 47(40): 341–35.
Yoo, C. K., J. H. Cho, H. J. Kwak, S. K. Choi, H. D. Chun, and I. Lee. 2001. Closed Loop Identification and Control Application for Dissolved Oxygen Concentration in a Full-Scale Coke Wastewater Treatment Plant. Water Sciene and Technology. 43: 207–214.
Zhang, P., M. Yuan, and H. Wang. 2006. Self-Tuning PID Based on Adaptive Genetic Algorithms with the Application of Activated Sludge Aeration Process. 6th World Congress on Intelligent Control and Automation.
Hong-Gui, H., Q. Jun-Fei, and C. Qi-Li. 2012. Model Predictive Control of Dissolved Oxygen Concentration Based on a Self-Organizing RBF Neural Network. Control Engineering Practice. 20: 465–476.
Belchiora, C. A. C., R. A. M. Araújoa, and J. A. C. Landeck. 2012. Dissolved Oxygen Control of the Activated Sludge Wastewater Treatment Process Using Stable Adaptive Fuzzy Control. Computers and Chemical Engineering. 37: 152–162.
Rocca, J. 2012. GA Optimized Fuzzy Logic Controller for the Dissolved Oxygen Concentration in a Wastewater Bioreactor. Master of Applied Science in Engineering, University of Guelph.
Badreddine, B. M., A. Zaremba, J. Sun, and F. Lin. 2001. Active Damping of Engine Idle Speed Oscillation by Applying Adaptive PID Control. The British Library.
Lin, F., R. D. Brant, and G. Saikalis. 2001. Self-tuning of PID Controllers By Adaptive Interaction. American Control Conference.
G. Saikalis and F. Lin. Adaptive Neural Network Control By Adaptative Interaction.
Brandt, R. D. and F. Lin. 1999. Adaptive Interaction and Its Application to Neural Networks. Information Sciences. 121: 201–215.
Badreddine, B. M. and F. Lin. 2001. Adaptive PID Controller For Stable Unstable Linear and Non-Linear Systems. IEEE International Conference on Control Applications.
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