Design of a modified model predictive control and composite control strategy for hydraulic turbine regulation system

As a critical component in hydropower systems, the Hydraulic Turbine Regulation System (HTRS) exhibits strong coupling characteristics that impose substantial challenges on control system design, necessitating the development of high-performance control strategies. To address the complex control requirements, this paper proposes an improved T-S fuzzy modeling method based on the Luenberger observer theory. It constructs a system model that combines high accuracy and simplicity. An enhanced MPC controller is designed to leverage the advantages of Model Predictive Control (MPC) in handling multivariable systems. Through receding horizon optimization, the MPC controller effectively mitigates system uncertainties and achieves high-precision trajectory tracking. Furthermore, a composite control framework integrating MPC and optimal adaptive fuzzy fractional-order PID (AFFOPID) is proposed by combining the properties of AFFOPID in robust control. The developed MPC-AFFOPID controller incorporates a dynamic compensation mechanism that synergistically combines the strengths of both strategies. This enables effective coordination of HTRS dynamic performance and operational constraints under varying conditions, overcoming the adaptability limitations of conventional single control strategies in complex scenarios. Simulation results show that the improved T-S fuzzy model significantly enhances modeling accuracy and parameter identification, reducing RMSE by up to 97 %. Compared to single control strategies, the proposed MPC-AFFOPID approach improves performance and response speed, cutting rise time by up to 85 % and boosting metrics by up to 80 %, confirming its effectiveness and engineering potential.