NDLI: Optimal control with actuator/sensor noise strengths related to feedback and Kalman gain

Content Provider	IEEE Xplore Digital Library
Author	Ruan, M. Choudhury, A.K.
Copyright Year	1992
Description	Author affiliation: Dept. of Electr. Eng., Howard Univ., Washington, DC, USA (Ruan, M.; Choudhury, A.K.)
Abstract	The linear quadratic Gaussian (LQG) method gives optimal results only when the noise covariance matrices of the actuators and sensors do not depend on feedback and Kalman gain matrices. However, in practical systems the strengths of the actuator and sensor noise generally depend on their capacities and the magnitudes of their signals, while the signal magnitudes and the required capacities depend on the feedback and Kalman gain matrices. Therefore, the covariance matrices of the actuator and sensor noises will actually depend on the feedback and Kalman gain matrices. This fact will make the LQG non-optimal or make the LQG system unstable. The authors investigate the problems of optimal control under the assumption that the noise covariance matrices of the actuators and sensors are functions of the capacities and the signal magnitude of the actuators and sensors, and thus are functions of the feedback and Kalman gain matrices. Under that assumption, the noise covariance matrices of the actuators and sensors are known before the feedback and Kalman gain matrices are designed. The new method will determine the optimal feedback and Kalman gain matrices and the required capacities of the actuators and sensors.<>
Starting Page	1836
Ending Page	1841
File Size	663531
Page Count	6
File Format	PDF
ISBN	0780308727
DOI	10.1109/CDC.1992.371112
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-12-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimal control Covariance matrix Feedback Kalman filters Capacitive sensors Gaussian noise Hydraulic actuators Sensor systems
Content Type	Text
Resource Type	Article

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