Fuente: PubMed "swarm" IEEE Trans Cybern. 2026 Jun 17;PP. doi: 10.1109/TCYB.2026.3692668. Online ahead of print.ABSTRACTThis article addresses the trajectory tracking control problem for four-wheel skid-steering small autonomous ground vehicles (FWSAGVs) subject to uncertain friction resistance, external disturbances, and parametric variations. Existing FWSAGV tracking methods usually focus on stability and robustness, but often lack explicit quantitative guarantees on transient and steady-state performance, or rely on relatively complex controller structures that are not well-suited for onboard implementation. To address this issue, a prescribed-performance fractional-order PI-like controller (PP-FOPIC) is proposed. By combining the prescribed performance control (PPC) with a low-complexity fractional-order PI-like structure, the proposed method explicitly constrains the tracking error evolution while avoiding complex online approximators and recursive backstepping designs. In addition, particle swarm optimization (PSO) is introduced to tune the key controller parameters automatically and reduce the subjectivity of manual tuning. Comparative simulations and real-world experiments demonstrate that the proposed method achieves better tracking accuracy, stronger robustness, and lower actuator overload than PP-IOPIC and proportional-integral-differential (PID). In particular, real-world hexagonal-trajectory experiments provide further evidence of its control effectiveness and practical applicability, with an average onboard execution time of 8.62 ms and a total actuator overload rate of 2.8740%.PMID:42308078 | DOI:10.1109/TCYB.2026.3692668