TY - GEN
T1 - An Optimal H2Controller Design Formulation and Solution Based on Chain-Scattering Description Approach
AU - Zhou, Yan Qi
AU - Tsai, Bo Cheng
AU - Ubadigha, Chinweze U.
AU - Tsai, Mi Ching
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents an approach for the design of optimal H2 feedback controllers using the Chain-scattering Description two-port framework. The proposed method enables a direct determination of the closed-loop poles from the state-space representation of a Standard Control Configuration plant. By leveraging the computer-aided design tools such as MATLAB/Simulink, the proposed solution facilitates efficient controller realization and analysis. The key contribution lies in the effective selection of weighting functions, which play a crucial role in determining the control system behavior. The presented formulation of weighting function selections aims to enhance the practical application of the optimal feedback controller design. The significance of this work extends to various engineering applications, promising advancements in control systems engineering, including the use of AI techniques for weighting function selection with the aim to drive innovation and enhance control system performance. Validation of the proposed approach using examples were provided.
AB - This paper presents an approach for the design of optimal H2 feedback controllers using the Chain-scattering Description two-port framework. The proposed method enables a direct determination of the closed-loop poles from the state-space representation of a Standard Control Configuration plant. By leveraging the computer-aided design tools such as MATLAB/Simulink, the proposed solution facilitates efficient controller realization and analysis. The key contribution lies in the effective selection of weighting functions, which play a crucial role in determining the control system behavior. The presented formulation of weighting function selections aims to enhance the practical application of the optimal feedback controller design. The significance of this work extends to various engineering applications, promising advancements in control systems engineering, including the use of AI techniques for weighting function selection with the aim to drive innovation and enhance control system performance. Validation of the proposed approach using examples were provided.
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U2 - 10.1109/CACS60074.2023.10326193
DO - 10.1109/CACS60074.2023.10326193
M3 - Conference contribution
AN - SCOPUS:85179837474
T3 - 2023 International Automatic Control Conference, CACS 2023
BT - 2023 International Automatic Control Conference, CACS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Automatic Control Conference, CACS 2023
Y2 - 26 October 2023 through 29 October 2023
ER -