Iterative Adaptive Critic Control Towards an Urban Wastewater Treatment Plant

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Iterative Adaptive Critic Control Towards an Urban Wastewater Treatment Plant

Wang, Ding / Ha, Mingming / Zhao, Mingming

The wastewaterIterative adaptive criticAdaptive critic control Wastewater treatmentis an important avenue of resources cyclic utilization when coping with the modern urban diseases. However, there always exist obvious nonlinearities and uncertainties within wastewater treatment systems, such that it is difficult to accomplish proper optimization objectives towards these complex unknown platforms. In this chapter, a data-driven iterative adaptive criticIterative adaptive critic (IAC) strategy is developed to address the nonlinear optimal control problemOptimal control problem. The iterative algorithm is constructed with a general framework, followed by convergence analysis and neural network implementation. Remarkably, the derived IAC control policy with an additional steady control input is also applied to a typical wastewater treatment plant, rendering that the dissolved oxygen concentration and the nitrate level are maintained at desired setting points. When compared with the incremental proportional–integral–derivativeProportional–integral–derivative method, it is found that faster response and less oscillation can be obtained during the IAC control process. Finally, the wastewater treatment problem is revisited by using the previous mixed driven control framework, with an emphasis on signally reducing control updating times.