Control Strategies for Linear Synchronous Motors

Linear synchronous motors (LSMs), particularly permanent‐magnet variants, have become pivotal in high-precision motion systems owing to their direct-drive nature, rapid response and high thrust density. Effective control strategies are essential to mitigate nonlinear effects such as cogging forces, friction, thermal drift and load variations that degrade performance. Traditional proportional–integral–derivative (PID) schemes offer simplicity and ease of implementation but often struggle with parameter uncertainties and external disturbances. Advanced methods explore sliding mode control (SMC) to exploit its inherent robustness against perturbations, albeit at the risk of chattering. Model predictive control (MPC) frameworks introduce optimisation over a finite horizon, enhancing trajectory tracking at the expense of increased computational demand. Observer-based approaches, including extended state observers (ESOs), estimate unknown disturbances in real time and compensate within feedback loops, thus improving disturbance rejection. Concurrently, data-driven and intelligent strategies such as model-free control (MFC) and neural-network-aided controllers bypass detailed motor modelling, promising adaptability under parameter drift. The integration of these techniques—often in hybrid forms, such as sliding mode with neural estimation or predictive control augmented by disturbance observers—has driven substantial gains in accuracy, robustness and dynamic bandwidth. These developments underpin applications ranging from semiconductor lithography stages to magnetic-levitation transport, where sub-micrometre precision and rapid settling are paramount.

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Control Strategies for Linear Synchronous Motors publication trend

The graph below shows the total number of articles in control strategies for linear synchronous motors across all publications each year (not limited to Nature Index journals).

Technical terms

Permanent magnet linear synchronous motor (PMLSM): A direct-drive motor using permanent magnets and synchronous excitation to generate linear motion without mechanical transmission elements.

Sliding mode control (SMC): A robust control technique that forces system trajectories onto a predefined sliding surface, offering insensitivity to parameter variations and disturbances.

Model-free control (MFC): A control paradigm that utilises real-time input–output data and ultra-local models to regulate systems without reliance on detailed physical parameters.

Extended state observer (ESO): An observer that estimates both system states and aggregated disturbances, facilitating real-time compensation within feedback controllers.

Model predictive control (MPC): An optimisation-based approach computing control actions by predicting future system behaviour over a finite horizon under constraints.

References

1. Model-Free Control of Permanent Magnet Synchronous Linear Motor Based on Ultra-local Model. Chinese Journal of Electrical Engineering (2024).
2. Extended State Observer-Based IMC-PID Tracking Control of PMLSM Servo Systems. IEEE Access (2021).
3. Multi-Kernel Neural Network Sliding Mode Control for Permanent Magnet Linear Synchronous Motors. IEEE Access (2021).