Model predictive control: MPC's role in the evolution of power electronics
The evolution of power electronics and its control has been mainly driven by industry
applications and influenced by the development achieved in several technologies, such as …
applications and influenced by the development achieved in several technologies, such as …
[HTML][HTML] Analysis and design of model predictive control frameworks for dynamic operation—An overview
This article provides an overview of model predictive control (MPC) frameworks for dynamic
operation of nonlinear constrained systems. Dynamic operation is often an integral part of …
operation of nonlinear constrained systems. Dynamic operation is often an integral part of …
Towards longitudinal and lateral coupling control of autonomous vehicles using offset free MPC
L Ge, Y Zhao, F Ma, K Guo - Control Engineering Practice, 2022 - Elsevier
Abstract Model predictive control (MPC) is widely used in the motion control of autonomous
vehicles. However, the conventional MPC relies on an accurate model and cannot achieve …
vehicles. However, the conventional MPC relies on an accurate model and cannot achieve …
Active safety control of automated electric vehicles at driving limits: A tube-based MPC approach
To enhance the active safety performance for automated electric vehicles (AEVs) at driving
limits, the collaborative control of four-wheel steering (4WS) and direct yaw-moment control …
limits, the collaborative control of four-wheel steering (4WS) and direct yaw-moment control …
Regularized and distributionally robust data-enabled predictive control
In this paper, we study a data-enabled predictive control (DeePC) algorithm applied to
unknown stochastic linear time-invariant systems. The algorithm uses noise-corrupted …
unknown stochastic linear time-invariant systems. The algorithm uses noise-corrupted …
[HTML][HTML] do-mpc: Towards FAIR nonlinear and robust model predictive control
Over the last decades, model predictive control (MPC) has shown outstanding performance
for control tasks from various domains. This performance has further improved in recent …
for control tasks from various domains. This performance has further improved in recent …
Nonlinear model predictive control based on a self-organizing recurrent neural network
HG Han, L Zhang, Y Hou… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a
self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure …
self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure …
Data-driven safety filters: Hamilton-jacobi reachability, control barrier functions, and predictive methods for uncertain systems
Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …
including the reliable integration of renewable energy sources into power grids, safe …
Trajectory tracking control of autonomous vehicle with random network delay
Z Luan, J Zhang, W Zhao… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Random network delay will introduce uncertainty into trajectory tracking model of the
autonomous vehicle, which seriously deteriorates the vehicle's control system stability and …
autonomous vehicle, which seriously deteriorates the vehicle's control system stability and …
[PDF][PDF] Model predictive control
HTOA YOUNG - 2015 - researchgate.net
A major breakthrough in power electronics, which started a revolution in the control of
power, was the thyristor, introduced by General Electric in 1957 [1]. The introduction of this …
power, was the thyristor, introduced by General Electric in 1957 [1]. The introduction of this …