Robust Fault Tolerant Control Based on Adaptive Dynamic Programming With Experience Replay for Wastewater Treatment Processes

Abstract

An essential component of the activated sludge method for wastewater treatment is the stable control of the dissolved oxygen (DO) concentration. However, the actuator failure and unavoidable external disturbances may cause deviations in the DO concentration, and even destabilize the system. In this article, a fault tolerant control approach utilizing adaptive dynamic programming (ADP) and experience replay (ER) is developed with the purpose of realizing robust control of the DO concentration under the influence of the actuator failure and external disturbances. First, a novel cost function considering actuator multiplicative failure and disturbances is constructed. Based on this cost function, the control law is designed, which can effectively suppress the adverse effects of the actuator failure and external disturbances on control performance. Second, the control input, failure input, and cost function are estimated via two action networks and one critic network. Specifically, the collaborative interaction of the three networks contributes to get the optimal robust control law. Third, an improved ER technique named disturbance-focused ER is designed for adjusting the critic network and action networks, where a metric rooted in disturbance magnitude and time-difference error is designed to dynamically adjust data and batch sizes, for effectively suppressing the external disturbances. Finally, the feasibility of the proposed fault tolerant control method based on ADP with ER is confirmed through simulation experiments.