# Large Scale Model Predictive Control with Neural Networks and Primal Active Sets

@article{Chen2019LargeSM, title={Large Scale Model Predictive Control with Neural Networks and Primal Active Sets}, author={Steven W. Chen and Tianyu Wang and Nikolay A. Atanasov and Vijay R. Kumar and Manfred Morari}, journal={Autom.}, year={2019}, volume={135}, pages={109947} }

## 36 Citations

### Approximate Dynamic Programming for Constrained Linear Systems: A Piecewise Quadratic Approximation Approach

- Mathematics, Computer ScienceArXiv
- 2022

This paper introduces an approach combining the two methodologies to overcome their individual limitations, and proposes an ADP method for CLQR problems using Model predictive control and a novel convex and piecewise quadratic neural network.

### Learning Models of Model Predictive Controllers using Gradient Data

- Mathematics, Computer ScienceIFAC-PapersOnLine
- 2021

### Design and Simulation of a Machine-learning and Model Predictive Control Approach to Autonomous Race Driving for the F1/10 Platform

- Computer Science
- 2020

### An Improved Data Augmentation Scheme for Model Predictive Control Policy Approximation

- Computer Science, MathematicsArXiv
- 2023

An improved data augmentation scheme based on predictor-corrector steps that enforces a user-defined level of accuracy, and shows that the error bound of the augmented samples are independent of the size of the neighborhood used for data augmented.

### Neural Operators for Bypassing Gain and Control Computations in PDE Backstepping

- Computer Science, Mathematics
- 2023

A framework for eliminating the computation of controller gain functions in PDE control is introduced, and the existence of a DeepONet approximation of the exact nonlinear continuous operator mapping PDE coefficient functions into gain functions is proved.

### Model-Free Adaptive Control of Hydrometallurgy Cascade Gold Leaching Process with Input Constraints

- Engineering, Materials ScienceACS omega
- 2023

Hydrometallurgy technology can directly deal with low grade and complex materials, improve the comprehensive utilization rate of resources, and effectively adapt to the demand of low carbon and…

### Deep Neural Network Based Model Predictive Control for Standoff Tracking by a Quadrotor UAV*

- Engineering2022 IEEE 61st Conference on Decision and Control (CDC)
- 2022

The standoff tracking requires an unmanned aerial vehicle (UAV) to loiter in a circular orbit above a target of interest. To achieve it, we propose a deep neural network (DNN) based model predictive…

### Guaranteed safe control of systems with parametric uncertainties via neural network controllers

- Computer Science2022 IEEE 61st Conference on Decision and Control (CDC)
- 2022

Mixed-integer problems that enable analyzing the behavior of the closed-loop system consisting of the highly nonlinear neural network controller and a linear system with parametric uncertainties are introduced.

### Standoff Tracking Using DNN-Based MPC with Implementation on FPGA

- Computer Science, MathematicsArXiv
- 2022

The hardware-in-the-loop (HIL) simulation with an FPGA@ 200MHz demonstrates that the DNN-based MPC scheme is a valid alternative to embedded implementations of MPC for addressing complex systems and applications which is impossible for directly solving the MPC optimization problems.

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