Nonlinear identification and control of a heat exchanger: a neural network approach

Abstract In this paper the potentials of neural networks-based control techniques are explored by applying a nonlinear generalized minimum variance control methodology to a simulated application example. In particular, reference is made to the control problem of regulating the output temperature of a liquid-satured steam heat exchanger by acting on the liquid flow-rate. Due to the non-minimum phase characteristic of the dynamics of the process, a simple inverting minimum variance controller is unsuitable. On the other hand, an effective solution is provided by a detuned model reference approach, which introduces a penalization factor in the control variable. A steady-state off-set error problem, caused by the neural network approximations, is tackled by means of an hybrid control structure, which combines a nonlinear integral action block with a neural controller. A comparison analysis is made to show the effectiveness of the proposed neural control schemes with respect to classical linear controllers.

[1]  Denis Dochain,et al.  Adaptive identification and control algorithms for nonlinear bacterial growth systems , 1984, Autom..

[2]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[3]  Riccardo Scattolini,et al.  Identification of a Liquid-Saturated Steam Heat Exchanger , 1982 .

[4]  L. Patnaik,et al.  Self-tuning minimum-variance control of nonlinear systems of the Hammerstein model , 1981 .

[5]  Keith D. C. Stoodley,et al.  Time Series Analysis: Theory and Practice I , 1982 .

[6]  Dale E. Seborg,et al.  Self-tuning controllers for nonlinear systems , 1987, Autom..

[7]  Lennart Ljung,et al.  Neural Networks in System Identification , 1994 .

[8]  Riccardo Scattolini,et al.  Self-Tuning Control of a Liquid-Saturated Steam Heat Exchanger , 1983 .

[9]  Baxter F. Womack,et al.  Discrete time adaptive control of linear systems with preload nonlinearity , 1984, Autom..

[10]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

[11]  Rutherford Aris,et al.  On bilinear estimation and control , 1981 .

[12]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

[13]  Jingxin Zhang,et al.  Explicit self-tuning control for a class of non-linear systems , 1989, Autom..

[14]  Luigi Piroddi,et al.  GMV technique for nonlinear control with neural networks , 1994 .

[15]  Riccardo Scattolini,et al.  Stochastic identification and digital control of a heat exchanger: a simulation test case☆ , 1984 .

[16]  Zhang Jingxin,et al.  Indirect adaptive suboptimal control for linear dynamic systems having polynomial nonlinearities , 1988 .

[17]  W. Rohsenow,et al.  Handbook of Heat Transfer , 1998 .

[18]  Richard S. Sutton,et al.  Neural networks for control , 1990 .

[19]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.