Robust task-space control of an autonomous underwater vehicle-manipulator system by PID-like fuzzy control scheme with disturbance estimator. (15th July 2017) - Londhe, P.S.; Mohan, S.; Patre, B.M.; Waghmare, L.M.
Abstract: This paper presents, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme for a task-space trajectory tracking control of an autonomous underwater vehicle-manipulator system (AUVMS) employed for deep-sea intervention tasks. The effectiveness of the proposed control scheme is numerically demonstrated on a planar underwater vehicle manipulator system (consisting of an underwater vehicle and 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 two main parts: first part uses a feed forward term to reinforce the control activity with extravagance from known desired acceleration vector and carries an estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. 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 system. To show the effectiveness of the proposed control scheme, comparison is made with linear and nonlinear 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. Abstract : Highlights: A robust nonlinear PID-like fuzzy task space tracking controller has been proposed. The general robust rule base structure design is presented. Efficacy of the proposed controller has been demonstrated on planar AUVMS. The proposed scheme shows better immunity to lumped uncertainty. The robustness of the proposed controller is evaluated over existing controllers.