Model predictive control: Recent developments and future promise
DQ Mayne - Automatica, 2014 - Elsevier
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Model predictive control in aerospace systems: Current state and opportunities
CONTROLLER design is more troublesome in aerospace systems due to, inter alia, diversity
of mission platforms, convoluted nonlinear dynamics, predominantly strict mission and …
of mission platforms, convoluted nonlinear dynamics, predominantly strict mission and …
NNV: the neural network verification tool for deep neural networks and learning-enabled cyber-physical systems
This paper presents the Neural Network Verification (NNV) software tool, a set-based
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
Multi-parametric toolbox 3.0
The Multi-Parametric Toolbox is a collection of algorithms for modeling, control, analysis,
and deployment of constrained optimal controllers developed under Matlab. It features a …
and deployment of constrained optimal controllers developed under Matlab. It features a …
An introduction to event-triggered and self-triggered control
Recent developments in computer and communication technologies have led to a new type
of large-scale resource-constrained wireless embedded control systems. It is desirable in …
of large-scale resource-constrained wireless embedded control systems. It is desirable in …
Control allocation—A survey
The control algorithm hierarchy of motion control for over-actuated mechanical systems with
a redundant set of effectors and actuators commonly includes three levels. First, a high-level …
a redundant set of effectors and actuators commonly includes three levels. First, a high-level …
Constrained zonotopes: A new tool for set-based estimation and fault detection
This article introduces a new class of sets, called constrained zonotopes, that can be used to
enclose sets of interest for estimation and control. The numerical representation of these …
enclose sets of interest for estimation and control. The numerical representation of these …
YALMIP: A toolbox for modeling and optimization in MATLAB
J Lofberg - 2004 IEEE international conference on robotics and …, 2004 - ieeexplore.ieee.org
The MATLAB toolbox YALMIP is introduced. It is described how YALMIP can be used to
model and solve optimization problems typically occurring in systems and control theory. In …
model and solve optimization problems typically occurring in systems and control theory. In …
Provably safe and robust learning-based model predictive control
Controller design faces a trade-off between robustness and performance, and the reliability
of linear controllers has caused many practitioners to focus on the former. However, there is …
of linear controllers has caused many practitioners to focus on the former. However, there is …
NNV 2.0: the neural network verification tool
This manuscript presents the updated version of the Neural Network Verification (NNV) tool.
NNV is a formal verification software tool for deep learning models and cyber-physical …
NNV is a formal verification software tool for deep learning models and cyber-physical …