This study proposes an improved super-twisting sliding mode (STSM) control method for a brushless doubly fed induction generator (BDFIG) used in standalone ship shaft power generation systems. Focusing on the problem of the low tracking accuracy of the power winding (PW) voltages caused by the parameter perturbation of BDFIG systems, a mismatched uncertain model of the BDFIG is constructed. Additionally, an improved STSM control method is proposed to address the power load variation and compensate for the mismatched uncertainty through virtual control technology. Based on the direct vector control of the control winding (CW), the proposed method ensured that the voltage amplitude error of the power winding could converge to the equilibrium point rather than the neighborhood. Finally, in the experimental investigation of the BDFIG-based ship shaft independent power system, the dynamic performance in the startup and power load changing conditions were analyzed. The experimental results show that the proposed improved STSM controller has a faster dynamic response and higher steady-state accuracy than the proportional integral control and the linear sliding mode control, with strong robustness to the mismatched uncertainties caused by parameter perturbations.

To improve the yaw-stability tracking accuracy and torque smoothness of distributed-drive electric vehicles (DDEVs) under high-speed double-lane-change maneuvers and crosswind disturbances, this paper proposes a multi-agent-system (MAS)-based direct yaw moment control (DYC) method using full-order terminal sliding mode (FOTSM) control. First, based on the vehicle yaw dynamics model and the vector superposition principle, the whole-vehicle yaw-rate and sideslip-angle responses are decomposed into the local contributions of four wheel agents. A leader–follower MAS tracking framework is then established, in which the yaw-stability reference model acts as the virtual leader, and the four wheel agents act as followers. Second, the yaw-rate error and sideslip-angle error are combined into an aggregated tracking error, thereby transforming yaw-stability control into a second-order nonlinear MAS tracking problem. A FOTSM DYC law is designed, and Lyapunov analysis proves that the closed-loop error system reaches the sliding surface and converges within finite time. Finally, hardware-in-the-loop experiments are conducted under double-lane-change maneuvers with and without crosswind disturbance. Compared with the uncontrolled case and a conventional MAS-based linear sliding mode controller, the proposed method reduces yaw-rate and sideslip-angle deviations, improves trajectory-tracking performance, maintains yaw stability under crosswind disturbance, and suppresses wheel-driving-torque chattering.