Predictive Control

Model Predictive Control (MPC) is an advanced control technique that optimizes a system's trajectory over a future time horizon by iteratively solving optimization problems. Current research emphasizes improving MPC's efficiency and robustness, particularly through integrating machine learning methods like reinforcement learning and neural networks (e.g., using transformers for faster computation or neural networks to approximate MPC solutions), and addressing challenges posed by model uncertainties and safety constraints using techniques such as control barrier functions and Bayesian optimization. These advancements are significantly impacting various fields, including robotics, autonomous vehicles, and energy systems, by enabling more efficient, safe, and adaptable control of complex systems.

Papers

December 4, 2023

Model Predictive Control Approach to Autonomous Formation Flight
Harun Celik, Dilara Kilinc
Predictive Control Model Predictive UAV Design Formation Flight

November 21, 2023

Model Predictive Control for Aggressive Driving Over Uneven Terrain
Tyler Han, Alex Liu, Anqi Li, Alex Spitzer, Guanya Shi, Byron Boots
Predictive Control Uneven Terrain Terrain Traversability Road Driving Vehicle Terrain Interaction Road Autonomy

November 15, 2023

Reinforcement Learning with Model Predictive Control for Highway Ramp Metering
Filippo Airaldi, Bart De Schutter, Azita Dabiri
Reinforcement Learning Predictive Control Traffic Management Ramp Metering

November 4, 2023

Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion
Donghoon Youm, Hyunyoung Jung, Hyeongjun Kim, Jemin Hwangbo, Hae-Won Park, Sehoon Ha
Predictive Control Robust Version Legged Robot Model Based

November 2, 2023

A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers
Anne van der Horst, Bas Meere, Dinesh Krishnamoorthy, Saray Bakker, Bram van de Vrande, Henry Stoutjesdijk, Marco Alonso, Elena Torta
Predictive Control Automatic Tuning M$ Base Controller Image Guided Simulation Based Optimization

October 31, 2023

Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictions
Siddharth H. Nair, Hotae Lee, Eunhyek Joa, Yan Wang, H. Eric Tseng, Francesco Borrelli
Autonomous Driving Autonomous Vehicle Multi Modal Predictive Control Path Planning Uncertain Reasoning Based Collision Modal Uncertainty Stochastic MPC

October 25, 2023

October 17, 2023

October 16, 2023

Forking Uncertainties: Reliable Prediction and Model Predictive Control with Sequence Models via Conformal Risk Control
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone
Predictive Control Conformal Prediction Epistemic Uncertainty Cyber Physical System Sequence Model Conformal Risk Control Reliable Prediction

October 15, 2023

October 12, 2023

Introducing a Deep Neural Network-based Model Predictive Control Framework for Rapid Controller Implementation
David C. Gordon, Alexander Winkler, Julian Bedei, Patrick Schaber, Jakob Andert, Charles R. Koch
Predictive Control Model Predictive Control Combustion System

October 10, 2023

Multi-Robot Cooperative Navigation in Crowds: A Game-Theoretic Learning-Based Model Predictive Control Approach
Viet-Anh Le, Vaishnav Tadiparthi, Behdad Chalaki, Hossein Nourkhiz Mahjoub, Jovin D'sa, Ehsan Moradi-Pari, Andreas A. Malikopoulos
Predictive Control Model Predictive Control Crowded Environment Multiple Robot Crowd Navigation Multi Robot Navigation

October 5, 2023

Generalized Benders Decomposition with Continual Learning for Hybrid Model Predictive Control in Dynamic Environment
Xuan Lin
Continual LEArning Predictive Control Dynamic Environment Model Predictive Control Bender Decomposition

September 28, 2023

Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction
Viet-Anh Le, Behdad Chalaki, Vaishnav Tadiparthi, Hossein Nourkhiz Mahjoub, Jovin D'sa, Ehsan Moradi-Pari
Predictive Control Trajectory Prediction Crowded Environment Social Navigation Crowd Navigation Multi Agent Motion Prediction

Predictive Control

Papers

Model Predictive Control Approach to Autonomous Formation Flight

Model Predictive Control for Aggressive Driving Over Uneven Terrain

Reinforcement Learning with Model Predictive Control for Highway Ramp Metering

Imitating and Finetuning Model Predictive Control for Robust and Symmetric Quadrupedal Locomotion

A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers

Predictive Control for Autonomous Driving with Uncertain, Multi-modal Predictions

Multi-Agent Reinforcement Learning-Based UAV Pathfinding for Obstacle Avoidance in Stochastic Environment

Model predictive control-based value estimation for efficient reinforcement learning

Signal Temporal Logic-Guided Model Predictive Control for Robust Bipedal Locomotion Resilient to Runtime External Perturbations

SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization

Forking Uncertainties: Reliable Prediction and Model Predictive Control with Sequence Models via Conformal Risk Control

Reinforcement Learning for Reduced-order Models of Legged Robots

Enhancing Task Performance of Learned Simplified Models via Reinforcement Learning

Introducing a Deep Neural Network-based Model Predictive Control Framework for Rapid Controller Implementation

Multi-Robot Cooperative Navigation in Crowds: A Game-Theoretic Learning-Based Model Predictive Control Approach

Generalized Benders Decomposition with Continual Learning for Hybrid Model Predictive Control in Dynamic Environment

Learning-Aided Warmstart of Model Predictive Control in Uncertain Fast-Changing Traffic

Incorporating Target Vehicle Trajectories Predicted by Deep Learning Into Model Predictive Controlled Vehicles

Tightly Joining Positioning and Control for Trustworthy Unmanned Aerial Vehicles Based on Factor Graph Optimization in Urban Transportation

Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction