期刊
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
卷 19, 期 1, 页码 101-111出版社
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-019-1027-z
关键词
Dead-zone; Kalman filter; random noise; robustness; sandwich systems
资金
- National Natural Science Foundation of China [61971120, 61671303]
- Shanghai Pujiang Program [18PJ1400100]
- project of the Science and Technology Commission of Shanghai [18070503000]
- Project of Fundamental Research Funds for the Central Universities
A robust-nonsmooth Kalman filtering approach is proposed for stochastic sandwich systems with dead-zones, which guarantees an upper bound on the variance of filtering error. The approach describes the system using a stochastic nonsmooth state-space function and utilizes a linearization approach based on nonsmooth optimization to approximate the system within a bounded region around the equilibrium point. The method also handles model uncertainty and performs state estimation for the system through robust-nonsmooth Kalman filtering.
In this paper, a robust-nonsmooth Kalman filtering approach for stochastic sandwich systems with dead-zone is proposed, which can guarantee the variance of filtering error to be upper bounded. In this approach, the stochastic sandwich system with dead-zone is described by a stochastic nonsmooth state-space function. Then, in order to approximate the nonsmooth sandwich system within a bounded region around the equilibrium point, a linearization approach based on nonsmooth optimization is proposed. For handling the model uncertainty caused by linearization and modeling, the robust-nonsmooth Kalman filtering method is proposed for state estimation of the stochastic sandwich system with dead-zones with model uncertainty. Finally, both simulation and experimental examples are presented for evaluating the performance of the proposed filtering scheme.
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