Tracking control based on model predictive control using Laguerre functions with pole optimization
D Jeong, SB Choi - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
This paper focused on improving a model predictive control (MPC) using Laguerre functions.
This study was conducted to achieve high performance while reducing the computational …
This study was conducted to achieve high performance while reducing the computational …
Learning convex terminal costs for complexity reduction in MPC
S Abdufattokhov, M Zanon… - 2021 60th IEEE …, 2021 - ieeexplore.ieee.org
Despite recent advances in computing hardware and optimization algorithms, solving model
predictive control (MPC) problems in real time still poses some technical challenges when …
predictive control (MPC) problems in real time still poses some technical challenges when …
Variable elimination in model predictive control based on K-SVD and QR factorization
A Bemporad, G Cimini - IEEE Transactions on Automatic …, 2021 - ieeexplore.ieee.org
For linearly constrained least-squares problems that depend on a vector of parameters, this
article proposes techniques for reducing the number of involved optimization variables. After …
article proposes techniques for reducing the number of involved optimization variables. After …
Reduction of the number of variables in parametric constrained least-squares problems
A Bemporad, G Cimini - arXiv preprint arXiv:2012.10423, 2020 - arxiv.org
For linearly constrained least-squares problems that depend on a vector of parameters, this
paper proposes techniques for reducing the number of involved optimization variables. After …
paper proposes techniques for reducing the number of involved optimization variables. After …
Fast adaptive regression-based model predictive control
E Mostafa, HA Aly, A Elliethy - Control Theory and Technology, 2023 - Springer
Abstract Model predictive control (MPC) is an optimal control method that predicts the future
states of the system being controlled and estimates the optimal control inputs that drive the …
states of the system being controlled and estimates the optimal control inputs that drive the …
Learning Lyapunov terminal costs from data for complexity reduction in nonlinear model predictive control
A classic way to design a nonlinear model predictive control (NMPC) scheme with
guaranteed stability is to incorporate a terminal cost and a terminal constraint into the …
guaranteed stability is to incorporate a terminal cost and a terminal constraint into the …
[图书][B] Robust real-time model predictive control for high degree of freedom soft robots
PE Hyatt - 2020 - search.proquest.com
This dissertation is focused on the modeling and robust model-based control of high degree-
of-freedom (DoF) systems. While most of the contributions are applicable to any difficult-to …
of-freedom (DoF) systems. While most of the contributions are applicable to any difficult-to …