Kyushu University Academic Staff Educational and Research Activities Database
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Yoshio Ebihara Last modified date:2024.04.03

Graduate School
Undergraduate School

 Reseacher Profiling Tool Kyushu University Pure
Academic Degree
Country of degree conferring institution (Overseas)
Field of Specialization
System and Control Theory
Total Priod of education and research career in the foreign country
Outline Activities
Analysis and Synthesis of Dynamical Systems Using Convex Optimization
Research Interests
  • Reliability and Stability Verification of Neural Networks by
    Advanced Optimization Technology
    keyword : neural network, reliability, stability, optimization theory,
  • Control System Analysis and Synthesis Using Convex Optimization
    keyword : Control Theory, Optimization Theory
Academic Activities
1. Y. Ebihara, H. Waki, V. Magron, N. H. A. Mai, D. Peaucelle, S. Tarbouriech, l2 induced norm analysis of discrete-time LTI systems for nonnegative input signals and its application to stability analysis of recurrent neural networks, European Journal of Control, 2021.10.
2. H Performance Limitation Analysis Using Semidefinite Programming.
3. Yoshio Ebihara, Dimitri Peaucelle, Denis Arzelier, Analysis and synthesis of interconnected positive systems, IEEE Transactions on Automatic Control, 10.1109/TAC.2016.2558287, 62, 2, 652-667, 2017.02, This paper is concerned with the analysis and synthesis of interconnected systems constructed from heterogeneous positive subsystems and a nonnegative interconnection matrix. We first show that admissibility, to be defined in this paper, is an essential requirement in constructing such interconnected systems. Then, we clarify that the interconnected system is admissible and stable if and only if a Metzler matrix, which is built from the coefficient matrices of positive subsystems and the nonnegative interconnection matrix, is Hurwitz stable. By means of this key result, we further provide several results that characterize the admissibility and stability of the interconnected system in terms of the Frobenius eigenvalue of the interconnection matrix and the weighted L1- induced norm of the positive subsystems again to be defined in this paper. Moreover, in the case where every subsystem is SISO, we provide explicit conditions under which the interconnected system has the property of persistence, i.e., its state converges to a unique strictly positive vector (that is known in advance up to a strictly positive constant multiplicative factor) for any nonnegative and nonzero initial state. As an important consequence of this property, we show that the output of the interconnected system converges to a scalar multiple of the right eigenvector of a nonnegative matrix associated with its Frobenius eigenvalue, where the nonnegative matrix is nothing but the interconnection matrix scaled by the steady-stage gains of the positive subsystems. This result is then naturally and effectively applied to formation control of multiagent systems with positive dynamics. This result can be seen as a generalization of a well-known consensus algorithm that has been basically applied to interconnected systems constructed from integrators..
Membership in Academic Society
  • The Iron and Steel Institute of Japan
Professional and Outreach Activities
IFAC Symposium on Robust Control Design, General Chair (2021)
IEEE Control Systems Society Board of Governors, Elected Member (2022-2024)
IFAC World Congress, IPC Co-Chair (2023).