Fuzzy Control of Drilling Rig Winch Motor Based on SAWS-SSA Algorithm

Abstract

This paper proposes an improved Sparrow Search Algorithm based on the self-avoiding random walk strategy as a fuzzy control method (SAWS-SSA) for rig winch motors in the complex oil rig electric control industry. The SAWS-SSA aims to accurately describe the system dynamics and improve the motor performance despite the large number of control-winch variables. During the startup of the three-phase asynchronous motor of the winch, the error value between the current feedback and thyristor trigger angle coupled with the periodic change rate was used as the input for the fuzzy control start. The fuzzy rules progressively reduce the components of the excitation current and iteratively calculate the difference between the input and feedback of the active power until the motor speed and torque are stabilized. To reduce the evaluation time of the optimization search, we optimized the heuristic affiliation function variables using an improved sparrow search algorithm equipped with a self-avoidance random walks strategy. Experimental verification confirms that SAWS-SSA outperforms other control algorithms in terms of the statistical error in the instantaneous dynamic response of the oil rig winch under a constant load and at different speeds.

Keywords

• Fuzzy control
• self-avoiding random walks strategy
• sparrow search algorithm
• fuzzy rules