Abstract
The thesis is devoted to developing an intelligent control system for controlling the distillate-feed ratio of a coal liquefaction unit. The main objective is to design a system that could optimize the performance of the unit and reduce energy consumption. A fuzzy logic based system is proposed, which utilizes real-time input information from the unit in combination with mathematical models to control the feed ratio. The fuzzy logic controller is tuned using the improved genetic algorithm method. The controller is then tested with experimental data to examine its performance. The results show that the proposed fuzzy logic based control system has the desired robustness and stability, and yields better performance than conventional control strategies.
1 Introduction
At present, the increasing demand for energy has led to a high focus on developing more efficient and environmentally friendly production technologies. One of the most promising approaches is the utilization of coal liquefaction technology. Due to its complexity and nonlinearities, it is difficult to control the distillate-feed ratio of the coal liquefaction unit, which is a crucial operating parameter. As a result, there is a need to develop an intelligent control system that can optimize the performance of the unit and reduce energy consumption.
2 Fuzzy Logic Based Control
This thesis proposes a fuzzy logic based control system for controlling the distillate-feed ratio of a coal liquefaction unit. The system is based on real-time input information from the unit, combined with mathematical models to estimate the target feed ratio. The fuzzy logic controller is tuned using the improved genetic algorithm method. The fuzzy logic based control system is designed to be robust and stable, while maintaining good performance.
3 System Design
The proposed fuzzy logic based system is based on the Takagi–Sugeno fuzzy inference system. This system uses heuristics and fuzzy logic to capture the nonlinear dynamics of the system. Additionally, real-time data is incorporated into the system to provide a better estimation of the target feed ratio. The fuzzy inference system is then tuned using an improved genetic algorithm method. The genetic algorithm is used to optimize the parameters of the system and improve the fuzzy logic controller’s performance.
4 System Testing
The fuzzy logic based control system is tested using real-time experimental data from a coal liquefaction unit. The results show that the proposed system is able to accurately track the target feed ratio, with a high degree of accuracy and stability. Furthermore, the fuzzy logic based control system outperforms conventional control strategies, such as PID and model predictive control.
5 Conclusion
In conclusion, this thesis has presented an intelligent control system for controlling the distillate-feed ratio of a coal liquefaction unit. A fuzzy logic based system is proposed, which utilizes real-time input information from the unit in combination with mathematical models to control the feed ratio. The fuzzy logic controller is tuned using the improved genetic algorithm method. The controller is then tested with experimental data to examine its performance. The results show that the proposed fuzzy logic based control system has the desired robustness and stability, and yields better performance than conventional control strategies.
