Development of multilayer neural network for real time temperature control system

Since last two decade a substantial amount of research has been reported in the field of identification and control of nonlinear dynamical systems using artificial neural networks. The work presented in this paper comprises the study of the development of multilayer neural network for real time temperature control system. Inverse dynamic modelling approach is used as a basic control strategy. The primary aim is to construct a network that allows for modeling of a global dynamics of a system. The study devoted to efficient identification and control design methods using neural network based nonlinear control for water bath temperature, and to implement them in a real world environment. The performance of the control systems was verified by simulations and with real-time experiments using pilot process.