Robust Adaptive Tracking Control of Autonomous Underwater Vehicle-Manipulator Systems

Author(s):  
Mohan Santhakumar ◽  
Jinwhan Kim

This paper proposes a new tracking controller for autonomous underwater vehicle-manipulator systems (UVMSs) using the concept of model reference adaptive control. It also addresses the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle and manipulator system based on Newton–Euler formulation scheme. The proposed adaptation control algorithm is used to estimate the unknown parameters online and compensate for the rest of the system dynamics. Specifically, the influence of the unknown manipulator mass on the control performance is indirectly captured by means of the adaptive control scheme. The effectiveness and robustness of the proposed control scheme are demonstrated using numerical simulations.

Author(s):  
JIANPING CAI ◽  
LUJUAN SHEN ◽  
FUZHEN WU

We consider a class of uncertain non-linear systems preceded by unknown backlash-like hysteresis, which is modelled by a differential equation. We propose a new state feedback robust adaptive control scheme using a backstepping technique and properties of the differential equation. In this control scheme, we construct a new continuous function to design an estimator to estimate the unknown constant parameters and the unknown bound of a ‘disturbance-like’ term. The transient performance of the output tracking error can be guaranteed by the introduction of pre-estimates of the unknown parameters in our controller together with update laws. We do not require bounds on the ‘disturbance-like’ term or unknown system parameters in this scheme. The global stability of the closed-loop system can be proved.


2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Mohan Santhakumar

This study addresses the detailed modeling and simulation of the dynamic coupling between an underwater vehicle and manipulator system. The dynamic coupling effects due to damping, restoring, and inertial effects of an underwater manipulator mounted on an autonomous underwater vehicle (AUV) are analyzed by considering the actuator and sensor characteristics. A model reference control (MRC) scheme is proposed for the underwater vehicle-manipulator system (UVMS). The effectiveness of the proposed control scheme is demonstrated using numerical simulations along with comparative study between conventional proportional-integral-derivative (PID) control. The robustness of the proposed control scheme is also illustrated in the presence of external disturbances and parameter uncertainties.


Author(s):  
Samir Ladaci ◽  
Abdelfatah Charef ◽  
Jean Loiseau

Robust Fractional Adaptive Control Based on the Strictly Positive Realness ConditionThis paper presents a new approach to robust adaptive control, using fractional order systems as parallel feedforward in the adaptation loop. The problem is that adaptive control systems may diverge when confronted with finite sensor and actuator dynamics, or with parasitic disturbances. One of the classical robust adaptive control solutions to these problems makes use of parallel feedforward and simplified adaptive controllers based on the concept of positive realness. The proposed control scheme is based on the Almost Strictly Positive Realness (ASPR) property of the plant. We show that this condition implies also robust stability in the case of fractional order controllers. An application to Model Reference Adaptive Control (MRAC) with a fractional order adaptation rule is provided with an implementable algorithm. A simulation example of a SISO robust adaptive control system illustrates the advantages of the proposed method in the presence of disturbances and noise.


Author(s):  
Huy Hung Nguyen ◽  
Van Tu Duong ◽  
Dae Hwan Kim ◽  
Hak Kyeong Kim ◽  
Sang Bong Kim

Motion control with high accuracy for each axial system is the fundamental requirement to reduce a synchronous motion error of a multi-axis system. Especially, designing a model-based controller for an uncertainty system with unknown parameters is not easy without using system identification. To overcome the mentioned issue, this article proposes a cross-coupling synchronous velocity controller using a backstepping-based model reference adaptive control scheme in an unsymmetrical biaxial winding system called a transformer winding system. The proposed controller deals not only with the uncertainty but also with the recursive structure of the system. The backstepping technique for the recursive structural system and the model reference adaptive control method for the uncertainty of the system are designed to stabilize two axial systems with unknown parameters. An auxiliary system is added to build the proposed controller for coping with input constraints of physical actuators. To improve the proposed controller’s ability to cope with external disturbances, a dead-zone modification is utilized to modify the adaptation laws to avoid the drift phenomenon. Moreover, a cross-coupling mechanism is integrated into the proposed controller to reduce the synchronous velocity error between the velocities of the biaxial winding system. The proposed controller is also transformed into discrete time to be run on a digital signal processor alone chip. The experimental results are shown to verify the high performance and efficiency of the proposed controller for practical applications.


A dynamic model of the underwater vehicle is usually established with parameters uncertainties due to the non-linear and time-varying nature of hydrodynamic forces from the surrounding fluid and external environmental disturbances. The paper investigates the motion control problem of the vehicle in tridimensional space based on model reference adaptive control. A developed autopilot consists of three independent controllers with a parameter adaptation law implemented. A control performance is guaranteed by suitably choosing design parameters. The effectiveness and robustness of the proposed control scheme for trajectory tracking in surge, depth and yaw dynamics is tested through simulations studies.


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