Advanced model predictive control framework for autonomous intelligent mechatronic systems: A tutorial overview and perspectives
This paper presents a review on the development and application of model predictive
control (MPC) for autonomous intelligent mechatronic systems (AIMS). Starting from the …
control (MPC) for autonomous intelligent mechatronic systems (AIMS). Starting from the …
Model predictive control of internal combustion engines: A review and future directions
An internal combustion engine (ICE) is a highly nonlinear dynamic and complex
engineering system whose operation is constrained by operational limits, including …
engineering system whose operation is constrained by operational limits, including …
Design and experimental validation of a robust model predictive control for the optimal trajectory tracking of a small-scale autonomous bulldozer
Trajectory tracking of an unmanned ground vehicle (UGV) is essential due to its extensive
construction, agriculture, and military applications. In this paper, we propose an efficient …
construction, agriculture, and military applications. In this paper, we propose an efficient …
Nonlinear model predictive path following controller with obstacle avoidance
In the control systems community, path-following refers to the problem of tracking an output
reference curve. This work presents a novel model predictive path-following control …
reference curve. This work presents a novel model predictive path-following control …
Flexible development and evaluation of machine‐learning‐supported optimal control and estimation methods via HILO‐MPC
Abstract Model‐based optimization approaches for monitoring and control, such as model
predictive control and optimal state and parameter estimation, have been used successfully …
predictive control and optimal state and parameter estimation, have been used successfully …
Learning-based predictive path following control for nonlinear systems under uncertain disturbances
R Yang, L Zheng, J Pan… - IEEE Robotics and …, 2021 - ieeexplore.ieee.org
Accurate path following is challenging for autonomous robots operating in uncertain
environments. Adaptive and predictive control strategies are crucial for a nonlinear robotic …
environments. Adaptive and predictive control strategies are crucial for a nonlinear robotic …
Nonlinear model predictive horizon for optimal trajectory generation
Y Al Younes, M Barczyk - Robotics, 2021 - mdpi.com
This paper presents a trajectory generation method for a nonlinear system under closed-
loop control (here a quadrotor drone) motivated by the Nonlinear Model Predictive Control …
loop control (here a quadrotor drone) motivated by the Nonlinear Model Predictive Control …
Performance study of model predictive control with reference prediction for real-time hybrid simulation
The accuracy of real-time hybrid simulation (RTHS) is greatly influenced by the inevitable
time delay and amplitude error due to the control plant dynamics. Several tracking …
time delay and amplitude error due to the control plant dynamics. Several tracking …
Constrained Gaussian process learning for model predictive control
Many control tasks can be formulated as tracking problems of a known or unknown
reference signal. examples are motion compensation in collaborative robotics, the …
reference signal. examples are motion compensation in collaborative robotics, the …
Safe Machine-Learning-Supported Model Predictive Force and Motion Control in Robotics
Many robotic tasks, such as human-robot interactions or the handling of fragile objects,
require tight control and limitation of appearing forces and moments alongside sensible …
require tight control and limitation of appearing forces and moments alongside sensible …