Optimal adaptive compensation control for a class of MIMO nonlinear systems with actuator failures

Xue Wu, Shaojie Zhang, Weifang Shuang, Erik Jan Van Kampen, Qiping Chu

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

An optimal adaptive compensation control scheme is proposed for a class of multi-input multi-output (MIMO) affine nonlinear systems with actuator failures. Considering stuck actuators and partial effectiveness failures, an adaptive dynamic programming method is adopted by using neural network to approximate the cost function. It adjust the weights of the neural network by using an online adaptive algorithm. An adaptive parameter adjustment law is designed to estimate the actuator failure coefficients. The proposed optimal adaptive compensation law can guarantee that the closed-loop system with actuator failures is stable and that the given reference signals are effectively tracked. Simulation results demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2016 UKACC International Conference on Control, UKACC Control 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781467398916
DOIs
Publication statusPublished - 7 Nov 2016
Event11th UKACC United Kingdom Automatic Control Council International Conference on Control, UKACC Control 2016 - Belfast, United Kingdom
Duration: 31 Aug 20162 Sep 2016

Conference

Conference11th UKACC United Kingdom Automatic Control Council International Conference on Control, UKACC Control 2016
CountryUnited Kingdom
CityBelfast
Period31/08/162/09/16

Keywords

  • actuator failure
  • MIMO nonlinear systems
  • optimal adaptive compensation control

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