Design of a Parameter Self-tuning PID Controller Based on an ER-SLP for a Variable-Frequency Air Compressor in a Rapid Deballasting System

A semisubmersible lifting and decommissioning platform is designed to fulfill the decommissioning requirements of offshore oilfield platforms. The rapid deballasting system is a critical component of the platform. During the course of operation, compressed air is injected into the column side ballast tank to maintain the stability of the platform. This is achieved by the air compressors. The objective of this study is to address the issues of high energy consumption, backward control methods and low efficiency in power frequency air compressors. To this end, frequency conversion is carried out via simulation. A novel fractional PID controller design, which is based on evidential reasoning (ER) and sequential linear programming (SLP) methodologies, is proposed. The method is based on the combination of an evidential reasoning (ER) rule and the optimization of the parameters of the ER rule through the use of a sequential linear programming (SLP) online optimization algorithm. The proposed algorithm is evaluated in comparison with power frequency control, a traditional PID controller, and a fractional PID controller within the context of a simulation model established within the Simulink environment. The evaluation is conducted under typical working conditions. The results of the simulation demonstrate that the ER fractional PID controller is more effective in balancing energy consumption and operation time during the operational process and exhibits superior control performance.