Safe learning in robotics: From learning-based control to safe reinforcement learning
The last half decade has seen a steep rise in the number of contributions on safe learning
methods for real-world robotic deployments from both the control and reinforcement learning …
methods for real-world robotic deployments from both the control and reinforcement learning …
Learning-based model predictive control: Toward safe learning in control
Recent successes in the field of machine learning, as well as the availability of increased
sensing and computational capabilities in modern control systems, have led to a growing …
sensing and computational capabilities in modern control systems, have led to a growing …
A computationally efficient robust model predictive control framework for uncertain nonlinear systems
In this article, we present a nonlinear robust model predictive control (MPC) framework for
general (state and input dependent) disturbances. This approach uses an online …
general (state and input dependent) disturbances. This approach uses an online …
Advanced model predictive control framework for autonomous intelligent mechatronic systems: A tutorial overview and perspectives
Y Shi, K Zhang - Annual Reviews in Control, 2021 - Elsevier
This paper presents a review on the development and application of model predictive
control (MPC) for autonomous intelligent mechatronic systems (AIMS). Starting from the …
control (MPC) for autonomous intelligent mechatronic systems (AIMS). Starting from the …
Fusion of machine learning and MPC under uncertainty: What advances are on the horizon?
This paper provides an overview of the recent research efforts on the integration of machine
learning and model predictive control under uncertainty. The paper is organized as a …
learning and model predictive control under uncertainty. The paper is organized as a …
Data-driven methods for building control—A review and promising future directions
ET Maddalena, Y Lian, CN Jones - Control Engineering Practice, 2020 - Elsevier
A review of the heating, ventilation and air-conditioning control problem for buildings is
presented with particular emphasis on its distinguishing features. Next, we not only examine …
presented with particular emphasis on its distinguishing features. Next, we not only examine …
[HTML][HTML] Robust adaptive MPC using control contraction metrics
We present a robust adaptive model predictive control (MPC) framework for nonlinear
continuous-time systems with bounded parametric uncertainty and additive disturbance. We …
continuous-time systems with bounded parametric uncertainty and additive disturbance. We …
Robust min-max model predictive vehicle platooning with causal disturbance feedback
Platoon-based vehicular cyber-physical systems have gained increasing attention due to
their potentials in improving traffic efficiency, capacity, and saving energy. However, external …
their potentials in improving traffic efficiency, capacity, and saving energy. However, external …
Trajectory tracking control of autonomous ground vehicles using adaptive learning MPC
K Zhang, Q Sun, Y Shi - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
In this work, an adaptive learning model predictive control (ALMPC) scheme is proposed for
the trajectory tracking of perturbed autonomous ground vehicles (AGVs) subject to input …
the trajectory tracking of perturbed autonomous ground vehicles (AGVs) subject to input …
Integrated battery thermal and energy management for electric vehicles with hybrid energy storage system: A hierarchical approach
Battery cooling is crucial for electric vehicles' thermal safety, energy consumption, and
battery life in hot climatic conditions. For electric vehicles with battery/supercapacitor hybrid …
battery life in hot climatic conditions. For electric vehicles with battery/supercapacitor hybrid …