Trajectory Tracking Control for Subsea Mining Vehicles Based on Fuzzy PID Optimised by Genetic Algorithms

In deep-sea mining operations, the seabed sediments (mud and sand) are very soft and slippery. This often causes the tracked vehicles to slip and go off course when they are driving on the seafloor. To solve the path-tracking problem for deep-sea mining vehicles, this study suggests a path-tracking controller that can adapt to the seabed environment. Firstly, the standard Stanley path-following algorithm is improved. We can use a simple model of the mining vehicle to work out how far it deviates from the straight and how much its direction changes. A special computer program, called a 'fuzzy algorithm', adjusts a machine's settings to deal with the conditions of the seabed and the path it needs to take. Secondly, a genetic algorithm optimises the fuzzy rules of the fuzzy PID controller. This solves the problem that the rules of fuzzy PID control are limited by the designer's experience. At the same time, a relationship was established between how fast the drive wheel accelerates and the slip rate. This was based on the dynamic model. This was done to prevent the drive wheel from accelerating too much and causing slippage. This stops the drive wheel from slipping by limiting how fast it can go. Finally, we created a system model in MATLAB/Simulink to analyse it. The results of the simulation show that the suggested control strategy works very well, making it an effective way to track the path of subsea mining vehicles.