Neural network modeling and generalized predictive control for an autonomous underwater vehicle

2008 ◽  
Author(s):  
Jianan Xu ◽  
Mingjun Zhang
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Autonomous Underwater Vehicle ◽  
Network Modeling ◽  
Underwater Vehicle ◽  
Neural Network Modeling ◽  
Generalized Predictive Control

scholarly journals Neural Network Predictive Control for Autonomous Underwater Vehicle with Input Delay

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Jiemei Zhao
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Control Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Path Tracking ◽  
Input Delay ◽  
Hydrodynamic Coefficients ◽  
Lyapunov Theorem ◽  
Neural Network Predictive Control

A path tracking controller is designed for an autonomous underwater vehicle (AUV) with input delay based on neural network (NN) predictive control algorithm. To compensate for the time-delay in control system and realize the purpose of path tracking, a predictive control algorithm is proposed. An NN is used to estimate the nonlinear uncertainty of AUV induced by hydrodynamic coefficients and the coupling of the surge, sway, and yaw angular velocity. By Lyapunov theorem, stability analysis is also given. Simulation results show the effectiveness of the proposed control strategy.

scholarly journals Efficient Multivariable Generalized Predictive Control for Autonomous Underwater Vehicle in Vertical Plane

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Xuliang Yao ◽  
Guangyi Yang
Keyword(s):  
Energy Consumption ◽  
Predictive Control ◽  
Autonomous Underwater Vehicle ◽  
Optimization Problems ◽  
Vertical Plane ◽  
Underwater Vehicle ◽  
Generalized Predictive Control ◽  
Time Step ◽  
Control Approach ◽  
Output Constraints

This paper presents the design and simulation validation of a multivariable GPC (generalized predictive control) for AUV (autonomous underwater vehicle) in vertical plane. This control approach has been designed in the case of AUV navigating with low speed near water surface, in order to restrain wave disturbance effectively and improve pitch and heave motion stability. The proposed controller guarantees compliance with rudder manipulation, AUV output constraints, and driving energy consumption. Performance index based on pitch stabilizing performance, energy consumption, and system constraints is used to derive the control action applied for each time step. In order to deal with constrained optimization problems, a Hildreth’s QP procedure is adopted. Simulation results of AUV longitudinal control show better stabilizing performance and minimized energy consumption improved by multivariable GPC.

Indirect Adaptive Generalized Predictive Control for an Autonomous Underwater Vehicle

2009 ◽  
Vol 419-420 ◽  
pp. 837-840
Author(s):  
Jian An Xu ◽  
Gui Fu Liu ◽  
Wen De Zhao ◽  
Ming Jun Zhang
Keyword(s):  
Predictive Control ◽  
Autonomous Underwater Vehicle ◽  
Moving Average ◽  
Underwater Vehicle ◽  
Least Square ◽  
Generalized Predictive Control ◽  
Average Model ◽  
Moving Average Model ◽  
Auto Regressive ◽  
Vehicle Motion

This paper investigates the application of indirect adaptive generalized predictive control to an autonomous underwater vehicle motion. A difference controlled auto-regressive integrated moving average model is used as the multi-step predictive model. Recursive least square method based on forgetting factors is used to identify the parameters of the difference controlled auto-regressive integrated moving average model. Simulation result shows that indirect adaptive generalized predictive control algorithm can be used to control the autonomous underwater vehicle motion.

Sign in / Sign up

Export Citation Format

Share Document