Increasing the efficiency of an electrostatic precipitator using fuzzy adaptive state-feedback controllers

Abstract

In recent years, electrostatic precipitators have been widely utilized in waste gas treatment processes across various plants and factories. Nevertheless, enhancing the efficiency of electrostatic precipitators requires additional research focused on the design of controllers to manage the input voltages. The present study introduces a fuzzy adaptive state-feedback controller for an electrostatic precipitator. Initially, the mathematical modeling of the electrostatic precipitator is examined. A state-feedback controller is developed using both the system error and its derivative to enhance the system's efficiency. The gradient descent method and the chain derivative rule are employed to adaptively adjust the control parameters. Subsequently, a fuzzy system comprising a singleton fuzzifier, product inference engine, and center average defuzzifier is implemented to enhance control performance. Ultimately, the simulation results are presented to demonstrate the effectiveness and capability of the proposed approach in comparison with other methods. More specifically, the recommended control strategy can quickly bring the system's performance to its desired efficiency level.