Model reduction methods for complex network systems
Network systems consist of subsystems and their interconnections and provide a powerful
framework for the analysis, modeling, and control of complex systems. However, subsystems …
framework for the analysis, modeling, and control of complex systems. However, subsystems …
Graph-theoretic analysis of power systems
In this paper, we present an overview of the applications of graph theory in power system
modeling, dynamics, coherency, and control. First, we study synchronization of generator …
modeling, dynamics, coherency, and control. First, we study synchronization of generator …
[HTML][HTML] The role of the license plate lottery policy in the adoption of Electric Vehicles: A case study of Bei**g
Policy is an influential factor to the purchase and usage of Electric Vehicles (EVs). This
paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in …
paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in …
Reduction of second-order network systems with structure preservation
This paper proposes a general framework for structure-preserving model reduction of a
second-order network system based on graph clustering. In this approach, vertex dynamics …
second-order network system based on graph clustering. In this approach, vertex dynamics …
Clustering approach to model order reduction of power networks with distributed controllers
This paper considers the network structure preserving model reduction of power networks
with distributed controllers. The studied system and controller are modeled as second-order …
with distributed controllers. The studied system and controller are modeled as second-order …
Nonlinear model reduction by deep autoencoder of noise response data
K Kashima - 2016 IEEE 55th conference on decision and …, 2016 - ieeexplore.ieee.org
In this paper a novel model order reduction method for nonlinear systems is proposed.
Differently from existing ones, the proposed method provides a suitable non-linear …
Differently from existing ones, the proposed method provides a suitable non-linear …
Model-free optimal control of linear multiagent systems via decomposition and hierarchical approximation
Designing the optimal linear quadratic regulator (LQR) for a large-scale multiagent system is
time consuming since it involves solving a large-size matrix Riccati equation. The situation is …
time consuming since it involves solving a large-size matrix Riccati equation. The situation is …
Model reduction of multiagent systems using dissimilarity-based clustering
This technical note investigates a model reduction scheme for large-scale multiagent
systems. The studied system is composed of identical linear subsystems interconnected by …
systems. The studied system is composed of identical linear subsystems interconnected by …
Fast online reinforcement learning control using state-space dimensionality reduction
In this article, we propose a fast reinforcement learning (RL) control algorithm that enables
online control of large-scale networked dynamic systems. RL is an effective way of …
online control of large-scale networked dynamic systems. RL is an effective way of …
Balanced truncation of networked linear passive systems
This paper studies model order reduction of multi-agent systems consisting of identical
linear passive subsystems, where the interconnection topology is characterized by an …
linear passive subsystems, where the interconnection topology is characterized by an …