Explore MATLAB source code curated for "广义预测控制" with clean implementations, documentation, and examples.
Generalized Predictive Control source program for SISO systems, addressing two scenarios: known plant model and unknown plant model, with implementation details for predictive algorithm and system identification
Implementation and testing of Generalized Predictive Control (GPC) algorithms through MATLAB simulations, with practical applications in robotics, autonomous vehicles, and aerospace systems
Application of Multiple Model Generalized Predictive Control (GMPC) in Circulating Fluidized Bed Boiler Bed Temperature Regulation
This program implements Generalized Predictive Control (GPC) for CARIMA models, featuring online parameter optimization and predictive control algorithms.
MATLAB code for fuzzy T-S predictive control implementing generalized predictive control based on fuzzy model identification using Takagi-Sugeno fuzzy systems and predictive control algorithms
Generalized Predictive Control Algorithm and Code Implementation
The self-tuning generalized predictive controller proposed by Clark et al. is a parameter model-based predictive control algorithm featuring time-domain optimized performance metrics integrated with identification and self-tuning mechanisms. This approach addresses inherent limitations in conventional self-tuning control. The provided code implements univariate GPC based on Diophantine equation derivation, featuring modular design for prediction horizon configuration and recursive parameter estimation.
Programming Simulation Implementation of Generalized Predictive Control Algorithm with Code Integration
Despite the extensive practical use of self-tuning controllers, their limitations are increasingly evident—particularly in systems with variable orders, time delays, and parameters. Consequently, developing controllers with robust performance is highly valuable for real-world applications. The generalized predictive control (GPC) self-tuning controller, proposed by Clark et al., is a parameter model-based predictive control algorithm. It employs a receding horizon optimization performance index and integrates system identification and self-tuning mechanisms to overcome inherent weaknesses, resulting in superior robustness. Key implementation aspects include online parameter estimation using recursive least squares (RLS) and predictive output computation via Diophantine equations.
This program implements generalized predictive control (GPC) for CARIMA (Controlled Auto-Regressive Integrated Moving Average) models with MATLAB-based algorithmic implementation.