Torpedo evasion simulation of underwater vehicle using fuzzy-logic-based tactical decision making in script tactics manager

Zhou

Journal of Applied Mathematics

et al. 2013

The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation.

Section: Qualitative Model In Stochastic Simulation a Complex Stochamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization

Zhou

Journal of Applied Mathematics

et al. 2013

“…Yildirim et al proposed a military deployment simulation based on the discrete-event system [13], with regard to a simulation whose aim is to find the most efficient solution for the transportation of military assets. The research of Son and Kim addressed a simulation of torpedo evasion of an underwater vehicle and focused on the decision-making logic of the underwater vehicle's evasion tactics [14]. However, former DM&S research also focused on the representation of behaviours of simulation entities as discrete-events, so that the results are limited in the discrete-event based system development.…”

Section: Introductionmentioning

confidence: 99%

Combat Simulation Framework Including Continuous Detection System

Ham¹,

Kwon²,

Park³

2014

Int. j. simul. model.

This paper presents a framework for an anti-air engagement simulation that includes continuous detection systems. According to resolutions, military simulations can be categorized into four different levels; campaign (war-game), mission, engagement, and engineering (natural-phenomenon). While the campaign and mission level systems are represented by discrete-event systems and the engineering level systems are represented by continuous-state systems, the engagement level systems may include both characteristics of the discrete and continuous systems. An engagement level system includes multiple combat entities represented by discrete-event systems; however, various performance parameters of combat entities (i.e. detection probability) belong to continuous-state systems. Although the detection probability can be computed by equations considering the synthetic environment, it cannot be directly used in a discrete-event system. To cope with the problem, we propose a glimpse probability suitable for the discrete-event systems and a construction procedure. The proposed framework is designed to be compatible with high-level architecture technology, and applied to antiair engagement simulations.

Advances in Mechanical Engineering

“…Literature 18 deeply studied the influence diagram and utilized multistage influence diagram to model the stand-alone air combat. Literature 19 studied tactical decision-making of the underwater vehicle to avoid torpedo. A method of tactical decision based on fuzzy logic was described.…”

Section: Introductionmentioning

confidence: 99%

“…A method of tactical decision based on fuzzy logic was described. Furthermore, literature 19 utilized Python language to script the decision-making process and carried out experiments on engineering application simulation platform. Literature 20 utilized fuzzy logic and Bayesian network to construct a situation assessment system, which included pilot mental model, aircraft platform model, sensor model, and data processing algorithm.…”

Section: Introductionmentioning

confidence: 99%

Research on unmanned combat aerial vehicle robust maneuvering decision under incomplete target information

Wang

Huang

Tang

2016

This article investigates the problem of designing a novel maneuvering decision-making method for the unmanned combat aerial vehicle. The design objective is to promote the real-time ability of decision-making method and solve the problem of uncertainty caused by incomplete target information. On the basis of statistics theory, a robust maneuvering decision method with self-adaptive target intention prediction is proposed. The robustness design is embedded in the membership function of the situation parameters. The reachable set theory and adaptive adjustment mechanism of the target state weight are used in the target intention prediction to promote the real-time ability. Simulations are conducted under the condition that the enemy aircraft perform both non-maneuvering and combat maneuvering. The results verify the good properties of the decision-making method, which can extend the survival time of the unmanned combat aerial vehicle when the enemy aircraft attacks, and short the taking position and attack time of the unmanned combat aerial vehicle when the enemy aircraft evades.