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Cementing is a critical link in oil and gas exploitation, in which slurry density control is particularly important. In this study, we examined a slurry mixing control system in order to solve the problem of time delays in the mixing system. The model of a slurry mixing system was built in accordance with the system’s structure. A Smith fuzzy PID (proportion integration differentiation) composite control solution is proposed herein, and the simulation results show that the adjustment time and overshoot are lower than those of the conventional PID control and Smith predictive compensation control. A genetic algorithm is utilized to optimize the quantization factor and scale factor of the Smith fuzzy PID controller. Following optimization, the rise time of the controller was found to be 0.45 s, which represents a decrease of 35.9%, the overshoot was reduced by 0.4%, and the stabilization time was reduced by 36.6%. Afterward, we built a cementing slurry mixing simulation experimental platform, and experiments were used to verify the feasibility and superiority of the Smith fuzzy PID controller optimized by the genetic algorithm in comparison with the conventional controllers. The study results thus provide a scientific basis for the engineering application of the autonomous control technology of the slurry mixing system in cementing units.
Gao et al. (Wed,) studied this question.