38 citations · 57 across the 17 of their papers we have counts for
18 papers
Contraction-Based Model Predictive Control using Bilinear Koopman Realizations with Proportional Error Bounds
Yuki Higuchi, Kazuhiro Sato
Data-driven model predictive control based on Koopman operator theory is a promising approach for constrained control of nonlinear systems with unknown dynamics. This paper propose…
Bilinear Koopman-Based Robust Model Predictive Control for Unknown Nonlinear Systems via Contraction Metrics
Yuki Higuchi, Kazuhiro Sato
Data-driven model predictive control (MPC) using Koopman operator theory is a promising approach for constrained control of unknown nonlinear systems. While linear Koopman realizat…
Generalized Resistance Geometry from Kron Reduction and Effective Resistance
Yosuke Kajiura, Kazuhiro Sato
We develop a generalized resistance geometry for unsigned directed graphs and signed undirected graphs based on Kron reduction and effective resistance. For unsigned strongly conne…
Controllability scores for selecting control nodes of large-scale network systems
Kazuhiro Sato, Shun Terasaki
To appropriately select control nodes of a large-scale network system, we propose two control centralities called volumetric and average energy controllability scores. The scores a…
Structured Output Feedback Control for Linear Quadratic Regulator Using Policy Gradient Method
Shokichi Takakura, Kazuhiro Sato
We consider the static output feedback control for Linear Quadratic Regulator problems with structured constraints under the assumption that system parameters are unknown. To solve…
Kron Reduction and Effective Resistance of Directed Graphs
Tomohiro Sugiyama, Kazuhiro Sato
In network theory, the concept of effective resistance is a distance measure on a graph that relates the global network properties to individual connections between nodes. In addit…
-Optimal Reduction of Positive Networks using Riemannian Augmented Lagrangian Method
Sota Misawa, Kazuhiro Sato
In this study, we formulate the model reduction problem of a stable and positive network system as a constrained Riemannian optimization problem with the -error objective func…
Stable Linear System Identification with Prior Knowledge by Riemannian Sequential Quadratic Optimization
Mitsuaki Obara, Kazuhiro Sato, Hiroki Sakamoto +2
We consider an identification method for a linear continuous time-invariant autonomous system from noisy state observations. In particular, we focus on the identification to satisf…
Minimal controllability problem on linear structural descriptor systems with forbidden nodes
Shun Terasaki, Kazuhiro Sato
We consider a minimal controllability problem (MCP), which determines the minimum number of input nodes for a descriptor system to be structurally controllable. We investigate the…
Minimal controllability problems on linear structural descriptor systems
Shun Terasaki, Kazuhiro Sato
We consider minimal controllability problems (MCPs) on linear structural descriptor systems. We address two problems of determining the minimum number of input nodes such that a de…
Reduced model reconstruction method for stable positive network systems
Kazuhiro Sato
We consider a reconstruction problem of a reduced stable positive network system with the preservation of the original interconnection structure based on an optimal model red…
Controllability maximization of large-scale systems using projected gradient method
Kazuhiro Sato, Akiko Takeda
In this work, we formulate two controllability maximization problems for large-scale networked dynamical systems such as brain networks: The first problem is a sparsity constraint…
Riemannian optimal identification method for linear systems with symmetric positive-definite matrix
Kazuhiro Sato, Hiroyuki Sato, Tobias Damm
This study develops identification methods for linear continuous-time symmetric systems, such as electrical network systems, multi-agent network systems, and temperature dynamics i…
Structure-preserving optimal model reduction based on Riemannian trust-region method
Kazuhiro Sato, Hiroyuki Sato
This paper studies stability and symmetry preserving optimal model reduction problems of linear systems which include linear gradient systems as a special case. The problem i…
Riemannian optimal model reduction of stable linear systems
Kazuhiro Sato
In this paper, we develop a method for solving the problem of minimizing the error norm between the transfer functions of original and reduced systems on the set of stable ma…
Optimal leader selection and demotion in leader-follower multi-agent systems
Kazuhiro Sato
We consider leader-follower multi-agent systems that have many leaders, defined on any connected weighted undirected graphs, and address the leader selection and demotion problems.…
Optimal Graph Laplacian
Kazuhiro Sato
This paper provides a construction method of the nearest graph Laplacian to a matrix identified from measurement data of graph Laplacian dynamics that include biochemical systems,…
Numerical solution of Lyapunov equations related to Markov jump linear systems
Tobias Damm, Kazuhiro Sato, Axel Vierling
We suggest and compare different methods for the numerical solution of Lyapunov like equations with application to control of Markovian jump linear systems. First, we consider fixe…