Gazebo Simulation of Autonomous Delivery Robot using Model Predictive Control for High-speed Mobility

Author(s):  
Seongyong Hur ◽  
David Kim ◽  
Chaehyun Lee ◽  
Minjun Choi ◽  
Seungchul Shin ◽  
...  
2014 ◽  
Vol 678 ◽  
pp. 377-381
Author(s):  
Long Sheng Wang ◽  
Hong Ze Xu

This paper addresses a position and speed tracking problem for high-speed train automatic operation with actuator saturation and speed limit. A nonlinear model predictive control (NMPC) approach, which allows the explicit consideration of state and input constraints when formulating the problem and is shown to guarantee the stability of the closed-loop system by choosing a proper terminal cost and terminal constraints set, is proposed. In NMPC, a cost function penalizing both the train position and speed tracking error and the changes of tracking/braking forces will be minimized on-line. The effectiveness of the proposed approach is verified by numerical simulations.


Author(s):  
P.E. Orukpe

In this paper, we apply model predictive control (MPC) based on mixed H2/H to active vibration control of the flexibility of railway vehicle to improve ride quality. However, the flexibility in the body of high-speed railway vehicles creates difficulties which in practice may result in the body structure being heavier than what it is supposed to be. The use of active suspension helps to model the vehicle and its flexibility in an effective manner. Conventional control approaches are compared with linear matrix inequality MPC technique using flexible-bodied railway vehicle as an example. The result indicates that the MPC technique performs better in improving ride comfort compared to the passive and classical techniques when flexible modes are present.


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