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Parameter Identification of Continuous-Time Systems Using Iterative Learning Control
Atsushi Fujimori,Shinsuke Ohara 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.2
This paper presents a system identification technique for continuous-time state-space system using the iterative learning control. The transfer function parameters are regarded as functions with respect to the state-space parameters which will be identified. The relationship between the state-space parameters and the response error is explicitly derived. An update law of the state-space parameters is proposed so as to improve the convergence speed. The effectiveness of the proposed identification technique is demonstrated by numerical examples.
Atsushi Fujimori,Shinsuke Ohara 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.3
This paper presents the order reduction for plant and controller models estimated by the joint input-outputapproach in the closed loop identification, named the controllability or observability intensity truncation (COIT)method in which the index for order reduction is the controllability intensity or the observability intensity. The useof these intensities depends on the estimated models obtained by the joint input-output approach. In the applicationof the closed loop identification with the balanced truncation (BT) and the COIT methods; a numerical exampleand an inverted pendulum experimental system, the COIT method appropriately reduces the order of the estimatedplant and controller models and is superior to the BT method.