A Salp Swarm Algorithm-based Model-free Adaptive Control Method and Its Application in Transformer Constant Temperature System

Aiming at the problem of temperature control of transformer, a salp swarm algorithm-based model free adaptive control (SSA-MFAC) algorithm is proposed. In SSA-MFAC, the nonlinear dynamics of the transformer temperature control system is linearized using the dynamic linearization technology and a time-varying parameters named pseudo-partial derivative (PPD). Then, an SSA-MFAC controller is designed, and the salp swarm algorithm (SSA) is introduced to automatically optimize the controller parameters. Based on the salps group behavior in the ocean, the SSA method achieves the goal of controller parameter optimization by simulating the predatory behavior of the salps. The main advantage of SSA-MFAC method is that the controller only makes use of the operation data of the transformer constant temperature oil bath refrigeration unit instead of the specific mathematical model, and the controller parameters are obtained by using the SSA algorithm instead of experience. The algorithm is proved to be effective based on MATLAB/Simulink simulation platform.