Task Space Control of an Autonomous Underwater Vehicle Manipulator System by Robust Single-Input Fuzzy Logic Control Scheme

• Published in: IEEE journal of oceanic engineering Vol. 42; no. 1; pp. 13 - 28
• Main Authors: Londhe, Pandurang S., Santhakumar, M., Patre, Balasaheb M., Waghmare, Laxman M.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Aerospace electronics; Autonomous underwater vehicle manipulator system (AUVMS); Autonomous underwater vehicles; Data acquisition; Fuzzy control; Fuzzy logic; Lyapunov stability; Manipulator dynamics; Offshore engineering; Proportional integral derivative; proportional–integral–derivative (PID) control; Robots; Robust control; single-input fuzzy logic control; Sliding mode control; Spatial analysis; task space control; Trajectory control; Uncertainty; Underwater vehicles; Vehicle dynamics; Vehicles
• ISSN: 0364-9059; 1558-1691
• DOI: 10.1109/JOE.2016.2548820

In this paper, a robust single-input fuzzy logic control Robust Single Input Fuzzy Logic Controller (RSIFLC) scheme is proposed and applied for task-space trajectory control of an autonomous underwater vehicle manipulator system (AUVMS) employed for underwater manipulation tasks. The effectiveness of the proposed control scheme is numerically demonstrated on a planar underwater vehicle manipulator system [consisting of an underwater vehicle and a two link rotary (2R) serial planar manipulator]. The actuator and sensor dynamics of the system are also incorporated in the dynamical model of an AUVMS. The proposed control law consists of a feedforward term to exaggerate the control activity with immoderation from the known desired acceleration vector and an estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics as a first part and a single-input fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system as a second part. The primary objective of the proposed control scheme is to track the given end-effector task space trajectory despite of external disturbances, system uncertainties, and internal noises associated with the AUVMS. To show the efficacy of the proposed control scheme, comparison is made with conventional fuzzy logic control (CFLC), sliding mode control (SMC), and proportional-integral-derivative (PID) controllers. Simulation results confirmed that with the proposed control scheme, the AUVMS can successfully track the given desired spatial trajectory and gives better and robust control performance.