Adaptive region tracking control for underwater vehicles with large initial deviation and general uncertainty

A region tracking control system is developed for underwater vehicles with large initial deviation and general uncertainty. The developed system is a nonlinear cascaded system, consisting of two subsystems in series. The fixed-gain controller of the first subsystem is designed to compensate for the region tracking error caused by the large initial deviation. In the second subsystem, the radial basis function neural network is adopted to approximate the general uncertainty along with the external disturbance and modelling uncertainty. According to the Lyapunov theory, the control law of the two subsystems and adaptive law of the second subsystem are derived to ensure the region tracking errors asymptotically converge to zero. The validity of the control system is verified by a series of comparisons on simulation results.

A Robust Region Control Approach for Simultaneous Trajectory Tracking and Physical Human-Robot Interaction

In this work, the uncertainty and disturbance estimator (UDE)-based robust region tracking controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and the compliant human-robot interaction simultaneously. Utilizing the back-stepping control approach, the UDE is seamlessly fused into the region tracking control framework to estimate and compensate the model uncertainty and external disturbance, such as unknown payload, unmodeled joint coupling effect and friction. The regional feedback error is derived from the potential function to drive the robot manipulator end-effector converging into the target region, where the robot manipulator can be passively manipulated based on the needs of human to achieve the compliant physical human-robot interaction. Extensive experimental studies are carried out with a universal robots 10 manipulator to validate the effectiveness of the proposed method for moving region trajectory tracking, handling unknown payload and compliant physical human-robot interaction. The superior robustness of the proposed approach is demonstrated by comparison with the existing controller under the adverse effect of unknown payload. The humanrobot interaction is achieved in a shared autonomy manner with the cooperation of the manipulator and the human subject to accomplish the temperature measurement task, where the variation in human-subject height and the complexity of aiming the thermometer are successfully accommodated.

Observer Based Region Tracking Control for Underwater Vehicles Without Velocity Measurement

This paper addresses the problem of region tracking control for underwater vehicles without velocity measurement in marine environment. For this case, an improved region tracking control strategy is proposed based on a Nussbaum state observer. In the proposed method, a Nussbaum state observer is developed to estimate the unmeasured velocity of the vehicle. And then an improved region tracking control strategy is presented by incorporating the estimated results of the state observer, such that the tracking errors satisfy the requirement of the prescribed boundaries. In addition, a RBF neural network is applied to approximate the unknown dynamics of the vehicle. It is verified that the estimated error and the tracking error are uniformly ultimately bounded. Finally, the proposed observer-based region tracking control strategy is applied on an underwater vehicle to perform simulation studies and compared with a traditional backstepping controller and a traditional region tracking controller based on a high-gain observer. The comparative simulation results demonstrate the effectiveness of the proposed region tracking control strategy.

Robust Region Tracking Control for a Robot Manipulator

n this work, the uncertainty and disturbance estimator (UDE)-based robust region reaching controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and complaint human robot interaction inside the target region. The regional feedback error is derived from the potential function to drive the robot manipulator end effector converging into the target region. Under the back-stepping control framework, the UDE is fused into the region tracking control law to estimate and compensate the model uncertainty and external disturbance. Both simulation and experimental studies are carried out with a universal robots (UR) 10 manipulator to demonstrate the effectiveness of the proposed method for moving target trajectory tracking, model uncertainty and external disturbance rejection, and compliant human robot interaction within the target region.

Robust Region Tracking Control for a Robot Manipulator

n this work, the uncertainty and disturbance estimator (UDE)-based robust region reaching controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and complaint human robot interaction inside the target region. The regional feedback error is derived from the potential function to drive the robot manipulator end effector converging into the target region. Under the back-stepping control framework, the UDE is fused into the region tracking control law to estimate and compensate the model uncertainty and external disturbance. Both simulation and experimental studies are carried out with a universal robots (UR) 10 manipulator to demonstrate the effectiveness of the proposed method for moving target trajectory tracking, model uncertainty and external disturbance rejection, and compliant human robot interaction within the target region.