Flatness-based model predictive control of six degree of freedom fixed-wing UAV

2019 ◽  
Author(s):  
R. Sandeepkumar ◽  
Ranjith Mohan
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Degree Of Freedom ◽  
Six Degree Of Freedom

Model Predictive Control of 2-Degree of Freedom Robotic Manipulator with Backlash

2020 ◽  
Author(s):  
Abdur Rauf ◽  
Fahad Mumtaz Malik ◽  
Hameed Ullah ◽  
Musayyab Ali
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Robotic Manipulator ◽  
Degree Of Freedom

Single Degree of Freedom Model Predictive Control with Variable Horizon

2020 ◽  
Author(s):  
Artemi Makarow ◽  
Christoph Rosmann ◽  
Torsten Bertram
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Degree Of Freedom ◽  
Single Degree Of Freedom ◽  
Single Degree

scholarly journals Dual Quaternion Based Close Proximity Operation for In-Orbit Assembly via Model Predictive Control

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Chuqi Sun ◽  
Yan Xiao ◽  
Zhaowei Sun ◽  
Dong Ye
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Coupling Effect ◽  
Suboptimal Control ◽  
Dual Quaternion ◽  
Close Proximity ◽  
The Stability ◽  
Six Degree Of Freedom ◽  
And Control

This paper studies the problem of guidance and control for autonomous in-orbit assembly. A six-degree-of-freedom (6-DOF) motion control for in-orbit assembly close proximity operation between a service satellite and a target satellite is addressed in detail. The dynamics based on dual quaternion are introduced to dispose the coupling effect between translation and rotation in a succinct frame, in which relevant perturbation and disturbance are involved. With the consideration of economical principle for fuel consume, a generic control system based on model predictive control (MPC) is then designed to generate a suboptimal control sequence for rendezvous trajectory considering actuator output saturation. The stability and robustness issues of the MPC-based control system are analyzed and proved. Numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed control scheme, while additional comparisons for diverse horizons of the MPC are further conducted.

Modeling and dynamic analysis of a 6 x 6 heavy military truck by adaptive model predictive control with application to NATO lane change test course

2020 ◽  
Vol 234 (13) ◽  
pp. 3128-3144
Author(s):  
Marcelo Andrés Acuña ◽  
Gustavo Simão Rodrigues ◽  
Rafael Vitor Guerra Queiroz ◽  
Elias Dias Rossi Lopes
Keyword(s):  
Model Predictive Control ◽  
Dynamic Analysis ◽  
Predictive Control ◽  
Degree Of Freedom ◽  
Adaptive Model ◽  
Double Line ◽  
Matlab Simulink ◽  
Longitudinal Dynamic ◽  
Adaptive Model Predictive Control ◽  
Lane Change Test

In this paper, the computer-aided vehicle dynamic analysis of a 6x6 heavy military truck is presented and examined. For the analysis, a MATLAB/Simulink® platform is used to design and model a truck. The vehicle configuration taken into account for the analysis is the powertrain (engine, gear box, transfer gear, differential), suspension, steering system and tire model according to the Pacekja 89’ formulation. In addition, the effect of the rolling resistance and drag is considered, in order to represent the vehicle behavior as real as possible. The longitudinal dynamic and lateral dynamic are formulated. First, the longitudinal dynamic model is established by means of implementation of the weight transfer function. The vehicles are considered as rigid bodies with 1 degree of freedom. Second, the vehicular planar model with three wheels, well known as bicycle model, is applied following the North Atlantic Treaty Organization double line change maneuver test reaching 3 degree of freedom. The driver behavior is represented by using an adaptive model predictive control varying the longitudinal velocity. The forces for braking, inertia of the rotating components, the energy lost in the powertrain, and the effect of dive squat and rollover. The numerical simulation results are shown and compared with a full-vehicle model formed by using Mechanical Simulation Corporation’s truckSIM®. There were chosen simulation scenarios applied to the model to observe the effects of different parameters concerning the dynamic behavior, and also prepared in truckSIM® environment. The main contributions of this article are the development of the vehicular model, through the use of block diagrams in a reliable and relatively simple programming code such as MATLAB/Simulink®, with innovative tools used in the control of autonomous vehicle driving and the flexibility to adapt said model to different environmental conditions and different vehicle parameters.

Automated Two-Degree-of-Freedom Model Predictive Control Tuning

2015 ◽  
Vol 54 (43) ◽  
pp. 10811-10824 ◽  
Author(s):  
Ning He ◽  
Dawei Shi ◽  
Jiadong Wang ◽  
Michael Forbes ◽  
Johan Backström ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Degree Of Freedom ◽  
Two Degree Of Freedom

Model predictive control of a multi-degree-of-freedom wave energy converter with model mismatch and prediction errors

2020 ◽  
Vol 212 ◽  
pp. 107724
Author(s):  
A.J. Hillis ◽  
J. Yardley ◽  
A.R. Plummer ◽  
A. Brask
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Degree Of Freedom ◽  
Prediction Errors ◽  
Energy Converter ◽  
Model Mismatch

scholarly journals A study of Model Predictive Control in terms of its structure and degree of freedom.

1987 ◽  
Vol 13 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Takeichiro Takamatsu ◽  
Tori Hashimoto ◽  
Masahiro Ohshima ◽  
Hiromu Ohno
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Degree Of Freedom
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