TY - GEN
T1 - Double command model-free hybrid control of a nonlinear CSTR
AU - Mohammadzaheri, Morteza
AU - Atrinejad, Hamidreza
AU - Kopaei, Mehdi Kasaee
AU - Behnia-Willison, Fariba
PY - 2010
Y1 - 2010
N2 - in this paper, a new methodology for feedforward-feedback control system design is proposed. Initially, the concept of control equilibrium point is introduced. Using this concept, the steady state control command is determined so as to maintain the desired situation of the system. Non-model-based feedforward control law is conducted on this basis using an artificial neural network. The feedback controller is a gain pushing the system towards the reference. In this article, the case study is the concentration control of a non-thermic Catalytic Stirred Tank Reactor (CSTR). Using the proposed control system, the value of feedback controller gain can be arbitrarily high with a guaranteed BIBO stability. The mathematical model of the system is used neither in design nor in stability analysis, and stability of the control system is addressed using some evident practical assumptions which can be extended to many other systems. In this case study, the level height of the reactor is not particularly subject to control but the control system is so designed that this variable never goes lower than a specified limit. The proposed method returns surprisingly good results in comparison with the results with a well-designed fuzzy control system.
AB - in this paper, a new methodology for feedforward-feedback control system design is proposed. Initially, the concept of control equilibrium point is introduced. Using this concept, the steady state control command is determined so as to maintain the desired situation of the system. Non-model-based feedforward control law is conducted on this basis using an artificial neural network. The feedback controller is a gain pushing the system towards the reference. In this article, the case study is the concentration control of a non-thermic Catalytic Stirred Tank Reactor (CSTR). Using the proposed control system, the value of feedback controller gain can be arbitrarily high with a guaranteed BIBO stability. The mathematical model of the system is used neither in design nor in stability analysis, and stability of the control system is addressed using some evident practical assumptions which can be extended to many other systems. In this case study, the level height of the reactor is not particularly subject to control but the control system is so designed that this variable never goes lower than a specified limit. The proposed method returns surprisingly good results in comparison with the results with a well-designed fuzzy control system.
KW - Artificial neural networks
KW - CSTR
KW - Feedforward control
KW - Nonlinear control
KW - Process control
UR - http://www.scopus.com/inward/record.url?scp=79952086637&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952086637&partnerID=8YFLogxK
U2 - 10.1109/CIMSiM.2010.58
DO - 10.1109/CIMSiM.2010.58
M3 - Conference contribution
AN - SCOPUS:79952086637
SN - 9780769542621
T3 - Proceedings - 2nd International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2010
SP - 227
EP - 232
BT - Proceedings - 2nd International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2010
T2 - 2nd International Conference on Computational Intelligence, Modelling and Simulation, CIMSim 2010
Y2 - 28 September 2010 through 30 September 2010
ER -