Control of a heat exchanger using neural network predictive controller combined with auxiliary fuzzy controller

Abstract The paper presents an advanced control strategy that uses the neural network predictive controller and the fuzzy controller in the complex control structure with an auxiliary manipulated variable. The controlled tubular heat exchanger is used for pre-heating of petroleum by hot water. The heat exchanger is modelled as a nonlinear system with the interval parametric uncertainty. The set point tracking and the disturbance rejection using intelligent control strategies are investigated. The control objective is to keep the outlet temperature of the pre-heated petroleum at a reference value. Simulations of control of the tubular heat exchanger are done in the Matlab/Simulink environment. The complex control structure with two controllers is compared with the conventional PID control, fuzzy control and NNPC. Simulation results confirm the effectiveness and superiority of the complex control structure combining the NNPC with the auxiliary fuzzy controller.

[1]  Robert W. Serth.  3 – Heat Exchangers , 2014 .

[2]  Mohammad Reza Jahed-Motlagh,et al.  Piecewise affine modeling and control of a boiler–turbine unit , 2010 .

[3]  Juraj Oravec,et al.  Robust Model Predictive Control of Heat Exchanger Network , 2013 .

[4]  Amin Gholami,et al.  Asphaltene precipitation of titration data modeling through committee machine with stochastically optimized fuzzy logic and optimized neural network , 2014 .

[5]  M. Bakošová,et al.  Robust Control of Heat Exchangers , 2012 .

[6]  Mehdi Shahbazian,et al.  The Design of Robust Soft Sensor Using ANFIS Network , 2014 .

[7]  Eduardo F. Camacho,et al.  Model predictive control in the process industry , 1995 .

[8]  Rui Araújo,et al.  Automatic extraction of the fuzzy control system by a hierarchical genetic algorithm , 2014, Eng. Appl. Artif. Intell..

[9]  Daniel Hladek,et al.  MULTI-ROBOT CONTROL SYSTEM FOR PURSUIT-EVASION PROBLEM , 2009 .

[10]  A. VasickaninovÃ,et al.  Control of a Heat Exchanger Using Neural Network Predictive Controller and Auxiliary Fuzzy Controller , 2014 .

[11]  Martin John Atkins,et al.  A derivative based method for cost optimal area allocation in heat exchanger networks , 2014 .

[12]  Gordon Hayward,et al.  Fuzzy logic applications. , 2003, The Analyst.

[13]  A. Markowski,et al.  Application of Fuzzy Logic Approach to Consequence Modeling in Process Industries , 2013 .

[14]  Michael Nikolaou,et al.  MPC: Current practice and challenges , 2009 .

[15]  A. VasickaninovÃ,et al.  Fuzzy Model-based Neural Network Predictive Control of a Heat Exchanger , 2010 .

[16]  Anis Sakly,et al.  Modeling and OnLine Control of Nonlinear Systems using Neuro- Fuzzy Learning tuned by Metaheuristic Algorithms , 2014 .

[17]  R. M. Darbra,et al.  Using fuzzy logic to introduce the human factor in the failure frequency Estimation of Storage Vessels in Chemical Plants , 2013 .

[18]  F. R. Salmasi,et al.  Control Strategies for Hybrid Electric Vehicles: Evolution, Classification, Comparison, and Future Trends , 2007, IEEE Transactions on Vehicular Technology.

[19]  Martin Horn,et al.  Energy-efficient fuzzy model-based multivariable predictive control of a HVAC system , 2014 .

[20]  Marcelo Embiruçu,et al.  Fuzzy control of a nylon polymerization semi-batch reactor , 2009, Fuzzy Sets Syst..

[21]  Guo-Yan Zhou,et al.  Optimum selection of compact heat exchangers using non-structural fuzzy decision method , 2014 .

[22]  Jean-Pierre Corriou,et al.  Optimal linear PI fuzzy controller design of a heat exchanger , 2008 .

[23]  Md. Mustafizur Rahman,et al.  Performance predictions of laminar heat transfer and pressure drop in an in-line flat tube bundle using an adaptive neuro-fuzzy inference system (ANFIS) model , 2014 .

[24]  Zhao Li,et al.  A novel neural network aided fuzzy logic controller for a variable speed (VS) direct expansion (DX) air conditioning (A/C) system , 2015 .

[25]  Radu-Emil Precup,et al.  A survey on industrial applications of fuzzy control , 2011, Comput. Ind..

[26]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[27]  V.M. Peri,et al.  Fuzzy logic control for an autonomous robot , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[28]  Ivo Babuška,et al.  Dealing with uncertainties in engineering problems using only available data , 2014 .

[29]  Ján Mikleš,et al.  Process Modelling, Identification, and Control , 2010 .

[30]  Jan Jantzen,et al.  Foundations of Fuzzy Control: A Practical Approach , 2013 .

[31]  Ramón Ferreiro García,et al.  Improving heat exchanger supervision using neural networks and rule based techniques , 2012, Expert Syst. Appl..

[32]  Guomin Cui,et al.  Efficient simultaneous synthesis for heat exchanger network with simulated annealing algorithm , 2015 .

[33]  Ahmed El Hajjaji,et al.  Advanced Takagi‒Sugeno Fuzzy Systems , 2014 .

[34]  Eid M. Al-Mutairi.  Optimal Design of Heat Exchanger Network in Oil Refineries. , 2010 .

[35]  D. Colorado,et al.  Inverse neural network for optimal performance in polygeneration systems , 2013 .

[36]  Jiří Jaromír Klemeš,et al.  Heat integration including heat exchangers, combined heat and power, heat pumps, separation processes and process control , 2012 .

[37]  S. Chakraverty,et al.  Non-probabilistic approach to investigate uncertain conjugate heat transfer in an imprecisely defined plate , 2013 .