## 1 Introduction
introduced a low-complexity error-surface prescribed performance control (ESPPC) for electro-hydraulic systems, addressing uncertainties and nonlinearity without the need for backstepping or complex approximators. Their experimental results confirmed that ESPPC can improve tracking performance and maintain system stability under variable conditions [17]. [PERSON], [PERSON] and [PERSON] et al. conducted a simulation study on a single-motor-one-pump (1M1P) controlled hydraulic cylinder, achieving passive load-holding functionality and system pressure control, which demonstrated system stability and strong load-holding performance in four-quadrant operation--offering an effective solution for practical applications of servo pump control [18]. [PERSON], [PERSON] et al. proposed an uncertain displacement-controlled system model for hydraulic actuators, utilizing PID and Ho controllers to verify system robustness under uncertain conditions, thereby significantly enhancing its performance in displacement control and disturbance rejection [19]. [PERSON], [PERSON] et al. developed a nonlinear Model Predictive Control (MPC) for variable-speed variable-displacement pumps, demonstrating substantial improvements in efficiency and flow tracking, which is meaningful for both energy efficiency and dynamic response [20]. [PERSON], [PERSON] et al. designed an extended sliding mode observer-based output feedback control scheme to address model uncertainties and external disturbances in the motion tracking of electro-hydrostatic actuators (EHAs), with the experimental results confirming its superiority in various operational scenarios [21]. Additionally, wind power generation faces inherent uncertainties, which further intensify these challenges. [PERSON], [PERSON] et al. investigated pitch angle control in wind turbine conversion systems under high wind speeds, highlighting that effective pitch control is crucial for protecting wind turbines from excessive winds [22]. [PERSON] and [PERSON] proposed a hierarchical fault-tolerant control using Model Predictive Control (MPC) to address pitch actuator faults, offering resilience against faults and maintaining system stability under adverse offshore conditions [23]. [PERSON], [PERSON] et al. developed a cyclic pitch control approach for Horizontal-Axis Wind Turbines (HAWTs) based on real-time inflow observation, which increased the power output and reduced fluctuations by adapting the pitch angles to local wind conditions [24]. [PERSON], [PERSON] et al. applied neural network fitting in pitch angle control of small wind turbines, achieving reliable power output control in high wind speeds through a MATLAB Simulink-supported control system [25]. [PERSON], [PERSON] and [PERSON] explored neural networks and reinforcement learning techniques for complex pitch control scenarios, particularly for offshore turbines exposed to unpredictable currents and waves, showing their effectiveness in adapting to variable wind and sea conditions [26]. [PERSON], [PERSON] and [PERSON], [PERSON] proposed an individual pitch control strategy to mitigate voltage flicker caused by wind turbine power fluctuations, significantly stabilizing the turbine's power output [27]. [PERSON], [PERSON] et al. developed a fuzzy logic-based pitch angle control for permanent magnet synchronous generator wind energy systems, demonstrating enhanced performance over traditional PI control, especially in high-wind conditions [28]. [PERSON], [PERSON] et al. introduced a single-blade pitch control based on SVM load estimation and LIDAR measurements, thereby reducing fatigue loads on wind turbines, which is essential for large-scale, high-power turbines [29]. [PERSON] and [PERSON] analyzed a variable-speed control strategy for direct-drive wind turbines using a variable gain pitch identification algorithm, effectively managing the generator speed during gusts to improve power generation stability and reduce turbine load [30].