An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system. (August 2020) - Liang, Haibo; Zou, Jialing; Zuo, Kai; Khan, Muhammad Junaid
Highlights: The wellhead back pressure control model is established and transfer function is calculated. An improved genetic algorithm optimization fuzzy PID controller is designed. Two experiments are designed to validate the great advantages of the developed model. Abstract: The throttle valve is the core equipment to managed pressure drilling (MPD) technology. PID controller is the most widely used throttle valve control algorithm. However, in the wellhead back pressure control system, the control of the throttle valve has strong nonlinearity and time variability. This makes precise closed-loop control of wellhead back pressure a challenge. The traditional controller needs to be improved in terms of control speed, stability and robustness. To overcome these shortcomings, this paper proposes an improved genetic algorithm optimization fuzzy controller. Firstly the wellhead back pressure control model is established and transfer function is calculated. Secondly, an improved genetic algorithm to optimize the highly nonlinear fuzzy control rules between the input and response in the fuzzy PID controller is designed. Finally, four traditional controllers are compared with the developed model to prove the method is optimal. The proposed controller has excellent performance in terms of time response parameters (such as rise time, adjustment time, overshoot, and steady-state error). The controller exhibits great advantages in terms of speed, stability, and robustness, which significantly improves the performance of the wellhead back pressure control system.