SET POINT TRACKING CONTROL OF A REMOTELY OPERATED VEHICLE USING MODEL PREDICTIVE CONTROL

This paper considers kinematics and dynamics of Remotely Operated Underwater Vehicle (ROV) to control position, orientation and velocity of the vehicle. Cascade control technique has been applied in this paper. The pole placement technique is used in inner loop of kinematics to stabilize the vehicle motions. Model Predictive control is proposed and applied in outer loop of vehicle dynamics to maintain position and velocity trajectories of ROV. Simulation results carried out on ROV shows the good performance and stability are achieved by using MPC algorithm, whereas sliding mode control loses its stability when ocean currents are high. Implementation of proposed MPC algorithm and stabilization of vehicle motions is the main contribution in this paper.

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Sliding Mode Based Predictive Controller of a Spheroidal Underwater Vehicle

10.3940/rina.ijme.2017.a2.418 ◽

2017 ◽

Vol Vol 159 (A2) ◽

Author(s):

M P R Prasad ◽

A Swarup

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Nuclear Reactor ◽

Sliding Mode ◽

Underwater Vehicle ◽

Control Technique ◽

Port Security ◽

Modeling And Control ◽

Vehicle Simulation ◽

Security Inspection

This paper focuses on hydrodynamic modeling and control of spheroidal underwater vehicle. The vehicle considered in this paper is appendage free and unstable. Water jet propulsion system is used in this vehicle. The dynamics of the vehicle is highly unstable due to munk moment. The spheroidal shape underwater robot is used in nuclear reactor inspection, port security inspection, defence and ocean surveillance where external appendages are not required. A new and innovative control technique, Sliding mode based model predictive control is introduced in this paper. Sliding mode control technique is used to stabilize the vehicle and once the vehicle model is stabilized it is easy to apply Model Predictive Control (MPC). Model Predictive control technique is used to control the heading of spheroidal underwater vehicle. Simulation results show that the Sliding mode based predictive control performance is better than simple PD control and state feedback controller.

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Notice of Removal Robust path tracking control using model predictive control and sliding mode control — Application to the JSAE-SICE benchmark problem

2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) ◽

10.1109/sice.2015.7285448 ◽

2015 ◽

Cited By ~ 1

Author(s):

Takatsugu Oda ◽

Kenichiro Nonaka ◽

Kazuma Sekiguchi

Keyword(s):

Model Predictive Control ◽

Sliding Mode Control ◽

Predictive Control ◽

Tracking Control ◽

Sliding Mode ◽

Path Tracking ◽

Benchmark Problem ◽

Mode Control ◽

Control Application

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Robust Path Tracking Control for Four-wheel Driving and Steering Vehicles Using Model Predictive Control and Sliding Mode Control

Transactions of the Society of Instrument and Control Engineers ◽

10.9746/sicetr.51.484 ◽

2015 ◽

Vol 51 (7) ◽

pp. 484-493 ◽

Cited By ~ 1

Author(s):

Takatsugu ODA ◽

Kenichiro NONAKA ◽

Kazuma SEKIGUCHI

Keyword(s):

Model Predictive Control ◽

Sliding Mode Control ◽

Predictive Control ◽

Tracking Control ◽

Sliding Mode ◽

Path Tracking ◽

Mode Control

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SLIDING MODE BASED PREDICTIVE CONTROLLER OF A SPHEROIDAL UNDERWATER VEHICLE

The International Journal of Maritime Engineering ◽

10.5750/ijme.v159ia2.1022 ◽

2021 ◽

Vol 159 (A2) ◽

Author(s):

M P R Prasad ◽

A Swarup

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Nuclear Reactor ◽

Sliding Mode ◽

Underwater Vehicle ◽

Control Technique ◽

Port Security ◽

Modeling And Control ◽

Vehicle Simulation ◽

Security Inspection

This paper focuses on hydrodynamic modeling and control of spheroidal underwater vehicle. The vehicle considered in this paper is appendage free and unstable. Water jet propulsion system is used in this vehicle. The dynamics of the vehicle is highly unstable due to munk moment. The spheroidal shape underwater robot is used in nuclear reactor inspection, port security inspection, defence and ocean surveillance where external appendages are not required. A new and innovative control technique, Sliding mode based model predictive control is introduced in this paper. Sliding mode control technique is used to stabilize the vehicle and once the vehicle model is stabilized it is easy to apply Model Predictive Control (MPC). Model Predictive control technique is used to control the heading of spheroidal underwater vehicle. Simulation results show that the Sliding mode based predictive control performance is better than simple PD control and state feedback controller.

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Explicit nonlinear model predictive control tracking control based on a sliding mode observer for a quadrotor subject to disturbances

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331219865816 ◽

2019 ◽

Vol 42 (2) ◽

pp. 214-227 ◽

Cited By ~ 2

Author(s):

Nadia Miladi ◽

Habib Dimassi ◽

Salim Hadj Said ◽

Faouzi M’Sahli

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Nonlinear Model ◽

Trajectory Tracking ◽

Tracking Control ◽

Sliding Mode ◽

High Gain ◽

Sliding Mode Observer ◽

Nonlinear Model Predictive Control ◽

Control Approach

In this paper, we propose an explicit nonlinear model predictive control (ENMPC) method based on a robust observer to solve the trajectory tracking problem for outdoor quadrotors. We take into consideration the external aerodynamic disturbances present in the dynamics of the Newton-Euler quadrotor model. To overcome the effects of these disturbances, a high gain observer combined with a first order sliding mode observer are proposed to estimate both the states and the unknown disturbances using the only positions and angular measurements of the quadrotor. The estimated signals are then used by the predictive controller in order to ensure the trajectory tracking objective. Despite the presence of bounded disturbances, the convergence of the composite controller (ENMPC technique with the latter observers) is guaranteed through a stability analysis. Theoretical results are validated with some numerical simulations showing the good performances of the proposed tracking control approach.

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An improved maximum power point tracking control approach for photovoltaic systems based on model predictive control with a condition-triggered strategy

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651815621834 ◽

2016 ◽

Vol 230 (3) ◽

pp. 277-288

Author(s):

Xilin Zhao ◽

Lijuan Yin ◽

Bo Fu ◽

Na Fang

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Tracking Control ◽

Maximum Power Point Tracking ◽

Photovoltaic Systems ◽

Maximum Power Point ◽

Control Approach ◽

Point Tracking ◽

Power Point Tracking ◽

Power Point

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Research on autonomous vehicle path tracking control considering roll stability

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407020942006 ◽

2020 ◽

Vol 235 (1) ◽

pp. 199-210

Author(s):

Fen Lin ◽

Shaobo Wang ◽

Youqun Zhao ◽

Yizhang Cai

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Vehicle Dynamics ◽

Tracking Control ◽

Autonomous Vehicle ◽

Path Tracking ◽

Proportional Integral Derivative ◽

Proportional Integral ◽

Vehicle Path ◽

Target Path

For autonomous vehicle path tracking control, the general path tracking controllers usually only consider vehicle dynamics’ constraints, without taking vehicle stability evaluation index into account. In this paper, a linear three-degree-of-freedom vehicle dynamics model is used as a predictive model. A comprehensive control method combining Model Predictive Control and Fuzzy proportional–integral–derivative control is proposed. Model Predictive Control is used to control the vehicle yaw stability and track the target path by considering the front wheel angle, sideslip angle, tire slip angles, and yaw rate during the path tracking. Fuzzy proportional–integral–derivative algorithm is adopted to maintain the vehicle roll stability by controlling the braking force of each tire. Co-simulation with CarSim and MATLAB/Simulink shows the designed controller has good tracking performance. The controller is smooth and effective and ensures handling stability in tracking the target path.

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