A Review of Recent Advances in Control Algorithms for Stewart Platforms
DOI:
https://doi.org/10.54097/r3ar0h87Keywords:
Stewart platform, parallel robot, motion control, model predictive control, sliding mode control, neural network, wave-induced motion compensationAbstract
The Stewart platform is a typical six-degree-of-freedom parallel mechanism characterized by high load-carrying capacity, high structural stiffness, a short error propagation chain, and fast dynamic response. It has been widely used in motion simulation, ship motion compensation, space payload pointing, precision machining, and multidimensional vibration control. Because the moving platform is cooperatively driven by six kinematic chains, its control system exhibits pronounced nonlinearity, strong coupling, and multivariable characteristics, and is affected by factors such as mechanical clearance, load variations, actuator saturation, sensor noise, and model parameter errors. Although conventional proportional-integral-derivative (PID) control has a simple structure and is easy to implement in engineering applications, it often struggles to simultaneously achieve high tracking accuracy, fast response, and stable operation under complex attitude variations and persistent external disturbances. In recent years, methods such as model predictive control, sliding mode control, adaptive control, robust control, neural networks, and reinforcement learning have gradually been introduced into Stewart platform systems. This review examines recent control strategies for Stewart platforms against four practical criteria: model requirements, disturbance rejection, constraint handling, and computational demand. The discussion also covers the validation methods and application conditions reported in marine compensation, motion simulation, aerospace positioning, precision machining, and vibration isolation. Particular attention is given to unresolved issues in modeling accuracy, sensing delay, real-time implementation, safety, and the generalization of learning-based controllers.
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