Research on the optimization of PID control of remotely operated underwater vehicle

Ant colony algorithm (ACA) is a heuristic evolutionary algorithm, which is based on bionic population, and PID controller of remote control underwater vehicle (ROV) can be optimized by it. Optimal combination of PID control parameters can be obtained by simulating the way ants find the shortest path, and then these parameters can be improved by ACA. The simulation results show that PID controller optimized by ACA will rise faster and overshoot smaller. The PID parameters improved by ACA will be better controlled than before.

[1]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[2]  Donald F. Towsley,et al.  On integrating fluid models with packet simulation , 2004, IEEE INFOCOM 2004.

[3]  Polly Huang,et al.  Enabling Large-scale Network Simulations: A Selective Abstraction Approach , 1999 .

[4]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[5]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[6]  Yanping Bai,et al.  The incorporation of an efficient initialization method and parameter adaptation using self-organizing maps to solve the TSP , 2006, Appl. Math. Comput..

[7]  M. Clerc,et al.  The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[8]  Ann Nowé,et al.  Colonies of learning automata , 2002, IEEE Trans. Syst. Man Cybern. Part B.