The role/application of Particle Swarm Optimization for Intruder Detection and Rescue Plans in Unmanned Underwater Vehicles

Abstract

In light of the development in computer controlled tools and expansion of integrated computing applications, lots of controller functions are turning to programming applications. In this study in view of a sea port security, an intrusion detection technique based on developed actuator model with the help of a controlling methodology dependent strategy has been designed. This research work gives simulation results on controlling of Underwater Unmanned Vehicles with the formation control of underwater swarm robots based on Assisting Mechanism Theory (AMT) and Integrated control Model (ICM). Such organization is really important in enhancement of surveillance, path planning, intruder and obstacle detection and error congestion in communication to remove uncertainty. The performance of ICM depends on complete swarm robot model to identify actuators. The ICM is responsible for development of swarm robot algorithm for movement control to guarantee surveillance, ensuring localization and detect intruders with the wipe-off of communication issues of the self-organized and decentralized behavior of multipurpose Particle Swarm Optimization (PSO) from the beginning time instance. This approach is also very helpful in serving as reference model for detecting multiple intruders and also in assisting mechanism theory of multiple Underwater Unmanned Vehicles. Such ICM controllers are prepared and compared with the Proportional Integral Derivative (PID) controllers in a diversity of simulations and gathered reaction found 12.37%, 8.69% and 12.09% better based on thrust produced in the propellers for surveillance.