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Research Article |

State Estimation based Inverse Dynamic Controller for Hybrid system using Artificial Neural Network

Author(s): Xiao Laui* and Rui-Lain Chua

Published In : International Journal of Electrical and Electronics Research (IJEER)        volume 8, Issue 1

Publisher : FOREX Publication

Published : 30 march 2020

e-ISSN : 2347-470X

Page(s) : 10-18

DOI: https://doi.org/10.37391/IJEER.080101

Abstract

State Estimation Based Inverse Dynamics Controller (SEBIDC), which utilizes an Artificial Neural Network (ANN) based state estimation scheme for nonlinear autonomous hybrid systems which are subjected to state disturbances and measurement noises that are stochastic in nature. A salient feature of the proposed scheme is that it offers better state estimates and hence a better control of non-measurable state variables with a nonlinear approach in correcting the a priori estimates by avoiding statistical linearization involved in existing approaches based on derivative free estimation methods. Simulation results guarantees significant reduction in Integral Square Error (ISE) and standard deviation (σ) of error, between the controlled variable and set point and control signal computation time when compared with best existing related work based on Unscented Kalman Filter (UKF) and Ensemble Kalman Filter (EnKF). Detailed analysis of the experimental results on real plant under different operating conditions such as servo and regulatory operations, initial condition mismatch, and different types of faults in the system, confirms robustness of proposed approach in these conditions and support the simulation results obtained. The main advantage of the proposed controller is that the control signal computation time is very much less than the selected sampling time of the process, so direct control of the plant is possible with this approach.

Keywords: Artificial Neural Network, Hybrid Dynamic Systems, State Estimation, Inverse Dynamics Controller.




Xiao Laui*, Research Scholar, University of Hong Kong, China; Email: xiaolauilaui@gmail.com

Rui-Lain Chua, Professor, University of Hong Kong, China

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Xiao Laui and Rui-Lain Chua (2020), Direct digital control scheme for controlling hybrid dynamic systems using ANN state estimator and inverse dynamics controller. IJEER 8(1), 1-9. DOI: 10.37391/IJEER.080101.