Performance comparison of estimation-based control schemes for hybrid systems

Abstract

In this paper, the authors have proposed an estimation-based control scheme. Artificial neural network and unscented Kalman filter are used for state estimation and inverse dynamics controller is implemented that utilizes the estimation of unmeasured state variables. The benchmark example taken for the analysis and implementation is nonlinear autonomous three-tank hybrid system and non-autonomous switched mode non-isothermal continuous stirred tank reactor, which are subjected to state and measurement noise. The performance comparison of both proposed estimation-based control scheme has been carried out and results are presented. Further, the proposed scheme is validated with three-tank hybrid system experimental setup.