Adaptive Generalized Predictive Control S-Function

This Adaptive Generalized Predictive Control S-Function implementation enables direct integration into SIMULINK environments for advanced predictive control studies. The program incorporates system identification and data analysis algorithms to forecast future system states, subsequently adjusting control strategies based on prediction outcomes for optimized system performance. The SIMULINK implementation framework facilitates streamlined predictive control research through MATLAB's S-function architecture, which handles real-time data processing and control law computations. The adaptive mechanism employs recursive parameter estimation techniques to continuously update the predictive model, while the generalized predictive control (GPC) algorithm calculates optimal control sequences using minimization of multi-step cost functions. This S-function's adaptability and generalized performance ensure reliable application across diverse systems, supporting customizable prediction horizons and control weighting factors for various industrial applications. The implementation includes configurable parameters for model order, control horizon, and weighting matrices, providing researchers with a versatile tool for control system design and validation.