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Jul 2026

Active suspension predictive control for high-speed trains based on disturbance feedforward and neural network residual compensation

Comparative tests show that the composite control strategy enhances the dynamic vibration suppression capabilities of high-speed trains working in complex, time-varying environments and enhancing robustness against model mismatch.

Hao-Feng Xie, Liang-Cheng Dai, Hong-Xing Gao et al. · 0 citations
Open access Jul 2026

Hybrid model predictive control and double integral backstepping for speed control of permanent magnet synchronous motors

A robust hybrid control approach integrating continuous control set model predictive control (CCS-MPC) with double integral backstepping (DIBC) is proposed for high-precision speed regulation of permanent magnet synchronous motors. The outer speed loop uses a DIBC controller that generates the reference q-axis current...

H. Sayaf, Katia Kouzi, L. Mokrani et al. · 0 citations
Open access Jul 2026

Model-free predictive control for PMSM based on a nonlinear autoregressive exogenous model and an adaptive recursive least squares algorithm

This paper proposes a novel nonlinear autoregressive with exogenous input-based adaptive recursive least squares model-free predictive control (NARX-ARLS-MFPC) strategy for permanent magnet synchronous motor (PMSM) drives. The core challenge addressed is the performance degradation of conventional model predictive cont...

Xiaolei Shi · 0 citations
Open access Aug 2026

Temporal-Feature-Enhanced Reinforcement Learning Control with Adaptive Speed-Loop Gain for PMSM Drives

Comparative simulations with conventional PI control and standard TD3 indicate that the proposed temporal-feature-enhanced reinforcement learning control approach for a PMSM drive system with adaptive regulation of the speed-loop gain improves transient response, reduces speed tracking error, and suppresses torque ripp...

Hongquan Zhang, Jingjun Cui, Zhihan Wu et al. · 0 citations
Open access Jul 2026

Fixed-time prescribed-performance path tracking control for intelligent vehicles based on adaptive neural network disturbance estimation

CarSim-Simulink-based co-simulation results validate the effectiveness of the proposed fixed-time prescribed-performance path tracking control method in improving both path tracking accuracy and stability.

Ping-Shu Ge, Chenyang Xu, Long-Xin Guan et al. · 0 citations

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