Rana, M.M., Xiang, W., and Choi, Bong Jun (2018) Wind turbine state-space model, state estimation and stabilisation algorithms. In: Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision. pp. 1235-1240. From: ICARCV 2018: 15th International Conference on Control, Automation, Robotics and Vision, 18-21 November 2018, Singapore.

PDF (Published Version) - Published Version Restricted to Repository staff only

 

1

1

Abstract

This paper develops a state estimation and stabilisation scheme for monitoring and controlling the wind turbine. Basically, the estimation scheme is designed considering the Bayesian tree network. The estimated system states are corrected in the forward and backward direction of this network where the estimation errors are enforced to minimise. Therefore, the estimated system state converges to the actual states as time goes by. Furthermore, the optimal feedback controller is designed. Interestingly, the proposed algorithms are applied to the environment-friendly wind turbine, and it shows that the developed methods can effectively estimate and stabilise the turbine states.

Actions (Repository Staff Only)

Item Control Page