Fuzzy Control Model with Automated Rule Base Generation for Artillery Systems in Game Simulators

This paper presents the development and validation of a fuzzy control model with automated rule base generation for artillery system actuators in game simulators. The proposed model integrates a bioinspired optimization mechanism based on the ant colony algorithm, enabling the automatic synthesis of efficient rule bases without relying on expert knowledge. This approach ensures adaptability and autonomy under uncertain conditions and provides logical transparency, allowing detailed analysis of control strategies. The model can be employed to simulate the decision-making behavior of virtual allies or adversaries, representing their different skill levels by adjusting reference models and objective functions at the design stage, thereby enhancing the realism in combat scenarios simulation. Experimental studies conducted on the example of an electric drive simulation model responsible for artillery mount barrel elevation demonstrated the superiority of the fuzzy model over a traditional PD controller in terms of robustness, efficiency and accuracy. The methodology presented in this paper can also be applied to hydraulic and other types of actuators.