A wave power generation power optimization method fusing anti-interference sliding mode and multi-dimensional prediction
By integrating the deep collaborative architecture ARSMC-MDMPCC, which combines disturbance-resistant sliding mode and multidimensional prediction, the shortcomings of wave power generation systems in dynamic response and global optimization are addressed, achieving efficient power capture and optimization under irregular sea waves.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUAIYIN INSTITUTE OF TECHNOLOGY
- Filing Date
- 2026-04-29
- Publication Date
- 2026-07-17
AI Technical Summary
Existing wave power generation systems have shortcomings in dynamic response and global optimization, making it difficult to meet the requirements of rapid tracking, strong anti-disturbance, no chattering and global optimization. Hybrid control architectures have low wave power capture efficiency under irregular wave conditions.
A wave power generation optimization method integrating disturbance-resistant sliding mode and multidimensional prediction is proposed. By constructing a deep collaborative architecture ARSMC-MDMPCC, combining the sliding mode control layer and the model prediction layer, a nonlinear fast convergence sliding mode surface, multidimensional feedback dynamic adjustment of switching gain, improved smoothing saturation function, and multidimensional objective optimization dynamic weighted cost function are adopted to achieve efficient selection and optimization of voltage vector.
It improves the power capture efficiency of wave power generation systems under irregular sea wave conditions, reduces the amount of computation and ensures optimization accuracy, and achieves a balance between fast tracking and global optimization.
Smart Images
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