Deep learning-based long-horizon MPC: robust, high performing, and computationally efficient control for PMSM drives
M Abu-Ali, F Berkel, M Manderla… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
This article presents a computationally efficient and high performing approximate long-
horizon model predictive control (MPC) for permanent magnet synchronous motors …
horizon model predictive control (MPC) for permanent magnet synchronous motors …
A stability governor for constrained linear–quadratic MPC without terminal constraints
This paper introduces a supervisory unit, called the stability governor (SG), that provides
improved guarantees of stability for constrained linear systems under Model Predictive …
improved guarantees of stability for constrained linear systems under Model Predictive …
A computable plant-optimizer region of attraction estimate for time-distributed linear model predictive control
J Leung, D Liao-McPherson… - 2021 American Control …, 2021 - ieeexplore.ieee.org
Time-distributed optimization is a suboptimal implementation strategy for reducing the
computational effort required to implement Model Predictive Control (MPC). Time-distributed …
computational effort required to implement Model Predictive Control (MPC). Time-distributed …
Encrypted MPC based on ADMM real-time iterations
MS Darup - IFAC-PapersOnLine, 2020 - Elsevier
Encrypted control enables confidential controller evaluations in cloud-based or networked
control systems. Technically, an encrypted controller is a modified control algorithm that is …
control systems. Technically, an encrypted controller is a modified control algorithm that is …
Deep learning-based approximate nonlinear model predictive control with offset-free tracking for embedded applications
The implementation of nonlinear model predictive control (NMPC) in applications with fast
dynamics remains an open challenge due to the need to solve a potentially non-convex …
dynamics remains an open challenge due to the need to solve a potentially non-convex …
Distributed control design for heterogeneous interconnected systems
This article presents scalable controller synthesis methods for heterogeneous and partially
heterogeneous systems. First, heterogeneous systems composed of different subsystems …
heterogeneous systems. First, heterogeneous systems composed of different subsystems …
When FPGAs meet ADMM with high-level synthesis (HLS): A real-time implementation of long-horizon MPC for power electronic systems
This paper presents a rapid and scalable implementation of an embedded model predictive
control (MPC) on a field-programmable gate arrays (FPGA) using a high-level synthesis …
control (MPC) on a field-programmable gate arrays (FPGA) using a high-level synthesis …
Improved Convergence Bounds For Operator Splitting Algorithms With Rare Extreme Errors
A Hamadouche, AM Wallace, JFC Mota - arXiv preprint arXiv:2306.16964, 2023 - arxiv.org
In this paper, we improve upon our previous work [24, 22] and establish convergence
bounds on the objective function values of approximate proximal-gradient descent (AxPGD) …
bounds on the objective function values of approximate proximal-gradient descent (AxPGD) …
Fast embedded tube-based MPC with scaled-symmetric ADMM for high-order systems: Application to load transportation tasks with UAVs
One of the most significant advantages of Model Predictive Control (MPC) is its ability to
explicitly incorporate system constraints and actuator specifications. However, a major …
explicitly incorporate system constraints and actuator specifications. However, a major …
Encrypted model predictive control in the cloud
MS Darup - Privacy in dynamical systems, 2020 - Springer
In this chapter, we focus on encrypted model predictive control (MPC) implemented in a
single cloud. In general, encrypted control enables confidential controller evaluations in …
single cloud. In general, encrypted control enables confidential controller evaluations in …