Javascript must be enabled to continue!
Intelligent-PID with PD Feedforward Trajectory Tracking Control of an Autonomous Underwater Vehicle
View through CrossRef
This paper investigates the model-free trajectory tracking control problem for an autonomous underwater vehicle (AUV) subject to the ocean currents, external disturbances, measurement noise, model parameter uncertainty, initial tracking errors, and thruster malfunction. A novel control architecture based on model-free control principles is presented to guarantee stable and precise trajectory tracking performance in the complex underwater environment for AUVs. In the proposed hybrid controller, intelligent-PID (i-PID) and PD feedforward controllers are combined to achieve better disturbance rejections and initial tracking error compensations while keeping the trajectory tracking precision. A mathematical model of an AUV is derived, and ocean current dynamics are included to obtain better fidelity when examining ocean current effects. In order to evaluate the trajectory tracking control performance of the proposed controller, computer simulations are conducted on the LIVA AUV with a compelling trajectory under various disturbances. The results are compared with the two degrees-of-freedom (DOF) i-PID, i-PID, and PID controllers to examine control performance improvements with the guaranteed trajectory tracking stability. The comparative results revealed that the i-PID with PD feedforward controller provides an effective trajectory tracking control performance and excellent disturbance rejections for the entire trajectory of the AUV.
Title: Intelligent-PID with PD Feedforward Trajectory Tracking Control of an Autonomous Underwater Vehicle
Description:
This paper investigates the model-free trajectory tracking control problem for an autonomous underwater vehicle (AUV) subject to the ocean currents, external disturbances, measurement noise, model parameter uncertainty, initial tracking errors, and thruster malfunction.
A novel control architecture based on model-free control principles is presented to guarantee stable and precise trajectory tracking performance in the complex underwater environment for AUVs.
In the proposed hybrid controller, intelligent-PID (i-PID) and PD feedforward controllers are combined to achieve better disturbance rejections and initial tracking error compensations while keeping the trajectory tracking precision.
A mathematical model of an AUV is derived, and ocean current dynamics are included to obtain better fidelity when examining ocean current effects.
In order to evaluate the trajectory tracking control performance of the proposed controller, computer simulations are conducted on the LIVA AUV with a compelling trajectory under various disturbances.
The results are compared with the two degrees-of-freedom (DOF) i-PID, i-PID, and PID controllers to examine control performance improvements with the guaranteed trajectory tracking stability.
The comparative results revealed that the i-PID with PD feedforward controller provides an effective trajectory tracking control performance and excellent disturbance rejections for the entire trajectory of the AUV.
Related Results
Sistem Kendali Hybrid Fuzzy-Pid pada Kinematika Robot Berkaki 4 Menggunakan Sensor Gyroscope
Sistem Kendali Hybrid Fuzzy-Pid pada Kinematika Robot Berkaki 4 Menggunakan Sensor Gyroscope
<p><em>Legged robots have attracted the attention of researchers because of their superior adaptation to complex environments compared to wheeled robots. Legged robots ...
Battery Energy Storage System (BESS) Modeling for Microgrid
Battery Energy Storage System (BESS) Modeling for Microgrid
In the age of technology, microgrids have become well known because of their capability to back up the grid when an unpleasant event is about to occur or during power disruptions, ...
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
High-fidelity modeling of redundant EMA and small angle displacement analysis under different controllers
An increasing number of applications of the electromechanical actuator (EMA) in the flight vehicle control system have required accurate dynamic models and control strategies. This...
Vehicle Theft Detection and Locking System using GSM and GPS
Vehicle Theft Detection and Locking System using GSM and GPS
A vehicle tracking system is very useful for tracking the movement of a vehicle from any location at any time. An efficient vehicle tracking system is designed and implemented for ...
Intelligent Vehicle Lateral Control Strategy Research based on Feedforward + Predictive LQR Algorithm with GA optimisation and PID compensation
Intelligent Vehicle Lateral Control Strategy Research based on Feedforward + Predictive LQR Algorithm with GA optimisation and PID compensation
Abstract
Targeting the lateral motion control problem in the intelligent vehicle autopilot structural system, this paper proposes a feedforward + predictive LQR algorithm f...
Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction
Trajectory Tracking Control for Intelligent Vehicles Based on Cut-In Behavior Prediction
For intelligent vehicles, trajectory tracking control is of vital importance. However, due to the cut-in possibility of adjacent vehicles, trajectory planning of intelligent vehicl...
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A Feedback‐Assisted Inverse Neural Network Controller for Cart‐Mounted Inverted Pendulum
A vast variety of neural network (NN)–based controllers use indirect adaptive control structures for their implementation, which primarily aims at estimating the nonlinear dynamics...
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies: A review and future outlook
Emerging underwater survey technologies are revolutionizing the way we explore and understand the underwater world. This review examines the latest advancements in underwater surve...

