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LQG modeling and GA control of structures subjected to earthquakes

  • Chen, ZY (Guangdong University of Petrochem Technol, Suh Sci) ;
  • Jiang, Rong (Guangdong University of Petrochem Technol, Suh Sci) ;
  • Wang, Ruei-Yuan (Guangdong University of Petrochem Technol, Suh Sci) ;
  • Chen, Timothy (Division of Engineering and Applied Science, California Institute of Technology)
  • Received : 2021.11.02
  • Accepted : 2022.03.07
  • Published : 2022.04.25

Abstract

This paper addresses the stochastic control problem of robots within the framework of parameter uncertainty and uncertain noise covariance. First of all, an open circle deterministic trajectory optimization issue is explained without knowing the unequivocal type of the dynamical framework. Then, a Linear Quadratic Gaussian (LQG) controller is intended for the ostensible trajectory-dependent linearized framework, to such an extent that robust hereditary NN robotic controller made out of the Kalman filter and the fuzzy controller is blended to ensure the asymptotic stability of the non-continuous controlled frameworks. Applicability and performance of the proposed algorithm shown through simulation results in the complex systems which are demonstrate the feasible to improve the performance by the proposed approach.

Keywords

Acknowledgement

The authors are grateful for the research grants given to Ruei-Yuan Wang from GDUPT talent introduction, Peoples R China under Grant No. 702-519208, the Projects of Talents Recruitment of GDUPT (NO. 2019rc098), and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (NO. 2021rc002) in Guangdong Province, Peoples R China, RY Wang from the Projects of Talents Recruitment of GDUPT (NO. 2019rc098), and Guangdong Provincial Key Lab.of Petrochemical Equipment and Fault Diagnosis, School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong 525000, China as well as to the anonymous reviewers for constructive suggestions.

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