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| Received:October 25, 2010Revised:September 18, 2011 |
| 基金项目:This work was supported by the National Grand Fundamental Research 973 Program of China (No. G2002CB312200). |
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| Decentralized adaptive iterative learning control for interconnected systems with uncertainties |
| Lili SUN,Tiejun WU |
| (Department of Control Science and Engineering, Zhejiang University) |
| Abstract: |
| In many applications, the system dynamics allows the decomposition into lower dimensional subsystems with interconnections among them. This decomposition is motivated by the ease and flexibility of the controller design for each subsystem. In this paper, a decentralized model reference adaptive iterative learning control scheme is developed for interconnected systems with model uncertainties. The interconnections in the dynamic equations of each subsystem are considered with unknown boundaries. The proposed controller of each subsystem depends only on local state variables without any information exchange with other subsystems. The adaptive parameters are updated along iteration axis to compensate the interconnections among subsystems. It is shown that by using the proposed decentralized controller, the states of the subsystems can track the desired reference model states iteratively. Simulation results demonstrate that, utilizing the proposed adaptive controller, the tracking error for each subsystem converges along the iteration axis. |
| Key words: Decentralized control Interconnected system Model reference Adaptive iterative learning control Model uncertainties |
