Research on fuzzy control of path tracking for underwater vehicle based on genetic algorithm optimization

Abstract The path tracking problem of underwater robots in different working conditions is studied. According to the analysis of the control model for underwater robots, a path tracking method for underwater robots based on a line-of-sight method is proposed. Based on the fuzzy control algorithm, a fuzzy controller is designed, which is further optimized by a genetic algorithm. The fuzzy control method developed is applied to the path tracking of a self-made underwater vehicle, and tested by both simulation and experiment. Results show that with the path control method based on the fuzzy controller optimized by the genetic algorithm ensures that the vehicle sails along the expected path. Also, the system shows strong robustness.

[1]  S. Prabhakar,et al.  Dynamics modeling and control of a variable length remotely operated vehicle tether , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[2]  John N. Lygouras,et al.  THETIS: an underwater remotely operated vehicle for water pollution measurements , 1998, Microprocess. Microsystems.

[3]  G. T. Donovan,et al.  Position Error Correction for an Autonomous Underwater Vehicle Inertial Navigation System (INS) Using a Particle Filter , 2012, IEEE Journal of Oceanic Engineering.

[4]  Zhang Yi,et al.  Stability of fuzzy control systems with bounded uncertain delays , 2002, IEEE Trans. Fuzzy Syst..

[5]  Hamed Kharrati,et al.  Optimized design of fractional-order PID controllers for autonomous underwater vehicle using genetic algorithm , 2015, 2015 9th International Conference on Electrical and Electronics Engineering (ELECO).

[6]  Sarat Kumar Patra,et al.  Design of real-time reconfigurable fuzzy logic controller with M-FRHC rule reduction technique , 2016, J. Intell. Fuzzy Syst..

[7]  Ming Zhang,et al.  Research of underwater navigation on a ROV with structure detection and decontamination , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

[8]  Xu Zhengping.  Design of Intelligent Greenhouse Fuzzy Controller Based on STM32 , 2013 .

[9]  P. A. DeBitetto.  Fuzzy logic for depth control of Unmanned Undersea Vehicles , 1995 .

[10]  Pi-Chun Chen,et al.  A non-line-of-sight error mitigation algorithm in location estimation , 1999, WCNC. 1999 IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466).

[11]  Morteza Montazeri-Gh,et al.  Application of genetic algorithm for optimization of control strategy in parallel hybrid electric vehicles , 2006, J. Frankl. Inst..

[12]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[13]  B. M. Huhman,et al.  Design of a compact, battery-powered rep-rate charger for an 88-kJ capacitor bank for EML applications , 2012, 2012 IEEE International Power Modulator and High Voltage Conference (IPMHVC).

[14]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[15]  A. J. Healey,et al.  Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicles , 1993 .