Research on Control Strategy of a Magnetorheological Fluid Brake Based on an Enhanced Gray Wolf Optimization Algorithm
Lili Dai, He Lu, Dezheng Hua, Xinhua Liu, Lifeng Wang, Qiang Li
Abstract
In order to improve the response characteristics of magnetorheological fluid brake (MRB) and reduce the braking fluctuation rate, an improved grey wolf optimization algorithm was proposed to adjust the parameters of the proportion integration differentiation (PID) controller. Firstly, an MRB system was designed and constructed, and its transfer function was determined. Moreover, by adopting the iterative method of logistic curve, an enhanced grey wolf optimization algorithm (EGWOA) was presented. Using the EGWOA, the parameters of the PID controller were optimized to improve the control performance of the system. Finally, the simulation and experiment were carried out. The results showed that EGWOA has a faster response output and overall better performance without overshoot compared with the conventional PID and grey wolf optimization algorithm (GWOA) PID controller.