Journal
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 63, Issue 4, Pages 1155-1162Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2017.2742661
Keywords
Extended Kalman filter (EKF); minimum entropy criterion; non-Gaussian stochastic nonlinear systems; tracking performance enhancement
Funding
- PNNL Control of Complex Systems Initiative
- National Natural Science Foundation of China [61621004, 61573022, 61333007]
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In this paper, a novel control algorithm is presented to enhance the performance of the tracking property for a class of nonlinear and dynamic stochastic systems subjected to non-Gaussian noises. Although the existing standard PI controller can be used to obtain the basic tracking of the systems, the desired tracking performance of the stochastic systems is difficult to achieve due to the random noises. To improve the tracking performance. an enhanced performance loop is constructed using the EKF-based state estimates without changing the existing closed loop with a PI controller. Meanwhile, the gain of the enhanced performance loop can be obtained based upon the entropy optimization of the tracking error. In addition, the stability of the closed loop system is analyzed in the mean-square sense. The simulation results are given to illustrate the effectiveness of the proposed control algorithm.
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