TY - JOUR
T1 - Neuro-adaptive sliding mode control for underground coal gasification energy conversion process
AU - Khattak, Mutahir
AU - Uppal, Ali Arshad
AU - Khan, Qudrat
AU - Bhatti, Aamer Iqbal
AU - Alsmadi, Yazan M.
AU - Utkin, Vadim I.
AU - Chairez, Issac
N1 - Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Due to the non-availability of model parameters, the model-base control of a nonlinear and infinite-dimensional underground coal gasification (UCG) process is a challenging task. In this paper, a robust neuro-adaptive sliding mode control (NASMC) is designed for the UCG process to maintain a desired heating value level. The unknown model parameters used in NASMC are estimated using the feed-forward neural network. Moreover, the controller also requires time derivatives of some model parameters, which are estimated by uniform robust exact differentiator. As the relative degree of the output with respect to the input is zero, therefore, to apply NASMC, the relative degree is increased to one. This approach maintains the desired heating value and provides insensitivity to input disturbance and model uncertainties. A comparison is also made between NASMC and an already designed conventional SMC. The simulation results show that NASMC exhibits better performance as compared to the conservative SMC design.
AB - Due to the non-availability of model parameters, the model-base control of a nonlinear and infinite-dimensional underground coal gasification (UCG) process is a challenging task. In this paper, a robust neuro-adaptive sliding mode control (NASMC) is designed for the UCG process to maintain a desired heating value level. The unknown model parameters used in NASMC are estimated using the feed-forward neural network. Moreover, the controller also requires time derivatives of some model parameters, which are estimated by uniform robust exact differentiator. As the relative degree of the output with respect to the input is zero, therefore, to apply NASMC, the relative degree is increased to one. This approach maintains the desired heating value and provides insensitivity to input disturbance and model uncertainties. A comparison is also made between NASMC and an already designed conventional SMC. The simulation results show that NASMC exhibits better performance as compared to the conservative SMC design.
KW - Relative degree
KW - feed-forward neural network
KW - neuro-adaptive sliding mode control
KW - underground coal gasification and energy conversion systems
KW - uniform robust exact differentiator
UR - http://www.scopus.com/inward/record.url?scp=85106274933&partnerID=8YFLogxK
U2 - 10.1080/00207179.2021.1909745
DO - 10.1080/00207179.2021.1909745
M3 - Artículo
AN - SCOPUS:85106274933
SN - 0020-7179
VL - 95
SP - 2337
EP - 2348
JO - International Journal of Control
JF - International Journal of Control
IS - 9
ER -